{ "results": [ { "id": "b52f2f0e53b69701d582ad2e96cd2a34", "title": "Sr. Machine Learning Engineer- Support", "employer_name": "Kenvue", "employer_slug": "kenvue", "location_text": "Asia Pacific, India, Karnataka, Bangalore", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://kenvue.wd5.myworkdayjobs.com/kenvue/job/Asia-Pacific-India-Karnataka-Bangalore/Sr-Machine-Learning-Engineer_2607042402W", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Machine Learning Engineer- Support Asia Pacific, India, Karnataka, Bangalore posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1944048/000194404826000030/kvue-20251228.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1944048/000194404826000030/kvue-20251228.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Retail", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.d5a99a9010d96fd6a6", "query_id": "gq_95345352ba55a57d7917", "job_id": "b52f2f0e53b69701d582ad2e96cd2a34", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b52f2f0e53b69701d582ad2e96cd2a34:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1944048/000194404826000030/kvue-20251228.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1944048/000194404826000030/kvue-20251228.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kenvue.wd5.myworkdayjobs.com/kenvue/job/Asia-Pacific-India-Karnataka-Bangalore/Sr-Machine-Learning-Engineer_2607042402W", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kenvue.wd5.myworkdayjobs.com/kenvue/job/Asia-Pacific-India-Karnataka-Bangalore/Sr-Machine-Learning-Engineer_2607042402W", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "9c0364f8da8f0d0242a01fc1199beb85", "title": "Technical Deployment Lead, Forward Deployed Engineering (FDE) - SF", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-02-26T21:10:46.893Z", "apply_url": "https://jobs.ashbyhq.com/openai/c5a99c73-c4c4-4321-a519-e0104dc54747", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Deployment Lead, Forward Deployed Engineering (FDE) - SF San Francisco, California, United States About the team OpenAI's Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development - working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You'll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You'll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": 25, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.a7268e51950d3070e7", "query_id": "gq_95345352ba55a57d7917", "job_id": "9c0364f8da8f0d0242a01fc1199beb85", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Deployment Lead, Forward Deployed Engineering (FDE) - SF San Francisco, California, United States About the team OpenAI's Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development - working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You'll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You'll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9c0364f8da8f0d0242a01fc1199beb85:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f7501f2447a9951606", "query_id": "gq_95345352ba55a57d7917", "job_id": "9c0364f8da8f0d0242a01fc1199beb85", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9c0364f8da8f0d0242a01fc1199beb85:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.030257b75a5a8e560f", "query_id": "gq_95345352ba55a57d7917", "job_id": "9c0364f8da8f0d0242a01fc1199beb85", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c5a99c73-c4c4-4321-a519-e0104dc54747", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c5a99c73-c4c4-4321-a519-e0104dc54747", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2a0d4e872c20738376b4d4c02ddff7f0", "title": "Machine Learning Engineer", "employer_name": "Ventas, Inc.", "employer_slug": "ventas", "location_text": "IL - Chicago", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-27T00:00:00.000Z", "apply_url": "https://ventas.wd503.myworkdayjobs.com/Ventas_Careers/job/IL---Chicago/Machine-Learning-Engineer_R0001509", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer IL - Chicago posted: Posted 16 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/740260/000074026026000006/vtr-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/740260/000074026026000006/vtr-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.a4400f35f26e6462f3", "query_id": "gq_95345352ba55a57d7917", "job_id": "2a0d4e872c20738376b4d4c02ddff7f0", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2a0d4e872c20738376b4d4c02ddff7f0:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/740260/000074026026000006/vtr-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/740260/000074026026000006/vtr-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://ventas.wd503.myworkdayjobs.com/Ventas_Careers/job/IL---Chicago/Machine-Learning-Engineer_R0001509", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://ventas.wd503.myworkdayjobs.com/Ventas_Careers/job/IL---Chicago/Machine-Learning-Engineer_R0001509", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "a30aa7faa7d80c0ebf74118aaf862168", "title": "Recruiting Optimization Manager", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 216000, "salary_max": 240000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 216000, "base_salary_max": 240000, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-19T19:44:33.904Z", "apply_url": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Recruiting Optimization Manager San Francisco, California, United States About the Team OpenAI's People team is committed to hiring, engaging, and supporting world-class talent to help safely build and deploy universally beneficial Artificial General Intelligence (AGI). The Recruiting Optimizations Manager is responsible for building and strengthening the systems, workflows, and operational infrastructure that make hiring at OpenAI fast, rigorous, and scalable. This role partners across recruiting, systems, and people teams to ensure recruiting foundations are efficient, reliable, auditable, and built to scale as OpenAI continues to grow rapidly and globally. This role leads Recruiting Operations optimization efforts across workflow design, operational automation, systems enablement, and scalable service operations. About the Role This role is focused on the systems and operational backbone of recruiting. The Recruiting Operations Manager will lead work across recruiting systems, workflow design, automation, process optimization, and data integrity to improve how hiring runs at scale. This role will translate business needs into durable operational solutions, drive improvements across the recruiting technology stack, and identify opportunities to reduce manual work through better tooling, automation, and process design. The right person will combine strong people management with systems thinking, operational rigor, and a practical approach to scaling high-quality recruiting infrastructure. This role is based in San Francisco, CA. We are not considering remote candidates at this time. In this role, you will: - Lead and develop a high-performing Recruiting Operations team, setting clear expectations, building strong judgment, and supporting career growth. - Own and improve the operational systems and workflows", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "hr", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b064fcc77049e61ad2", "query_id": "gq_95345352ba55a57d7917", "job_id": "a30aa7faa7d80c0ebf74118aaf862168", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Recruiting Optimization Manager San Francisco, California, United States About the Team OpenAI's People team is committed to hiring, engaging, and supporting world-class talent to help safely build and deploy universally beneficial Artificial General Intelligence (AGI). The Recruiting Optimizations Manager is responsible for building and strengthening the systems, workflows, and operational infrastructure that make hiring at OpenAI fast, rigorous, and scalable. This role partners across recruiting, systems, and people teams to ensure recruiting foundations are efficient, reliable, auditable, and built to scale as OpenAI continues to grow rapidly and globally. This role leads Recruiting Operations optimization efforts across workflow design, operational automation, systems enablement, and scalable service operations. About the Role This role is focused on the systems and operational backbone of recruiting. The Recruiting Operations Manager will lead work across recruiting systems, workflow design, automation, process optimization, and data integrity to improve how hiring runs at scale. This role will translate business needs into durable operational solutions, drive improvements across the recruiting technology stack, and identify opportunities to reduce manual work through better tooling, automation, and process design. The right person will combine strong people management with systems thinking, operational rigor, and a practical approach to scaling high-quality recruiting infrastructure. This role is based in San Francisco, CA. We are not considering remote candidates at this time. In this role, you will: - Lead and develop a high-performing Recruiting Operations team, setting clear expectations, building strong judgment, and supporting career growth. - Own and improve the operational systems and workflows", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:a30aa7faa7d80c0ebf74118aaf862168:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4fd76f2afb05714651", "query_id": "gq_95345352ba55a57d7917", "job_id": "a30aa7faa7d80c0ebf74118aaf862168", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:a30aa7faa7d80c0ebf74118aaf862168:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.0c9997f467af9863f7", "query_id": "gq_95345352ba55a57d7917", "job_id": "a30aa7faa7d80c0ebf74118aaf862168", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2f47bf5e9464f9cd3bfcbe11370a0efc", "title": "AI Engineer - AI, Data & Platforms", "employer_name": "Stage", "employer_slug": "stage", "location_text": "Gurugram", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://www.kkr.com/careers/career-opportunities/post?gh_jid=6016119004", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer - AI, Data & Platforms Gurugram", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c5f1bfde2e0c2ea6e6", "query_id": "gq_95345352ba55a57d7917", "job_id": "2f47bf5e9464f9cd3bfcbe11370a0efc", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2f47bf5e9464f9cd3bfcbe11370a0efc:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.kkr.com/careers/career-opportunities/post?gh_jid=6016119004", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.kkr.com/careers/career-opportunities/post?gh_jid=6016119004", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "7b67a2115e7a0f82884335689329ca90", "title": "Deep learning Engineer", "employer_name": "STMicroelectronics", "employer_slug": "stmicroelectronics", "location_text": "Greater Noida, India | Bangalore, India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://stmicroelectronics.eightfold.ai/careers/job/563637172189717", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Deep learning Engineer Greater Noida, India | Bangalore, India", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.688fdbf382d336b71b", "query_id": "gq_95345352ba55a57d7917", "job_id": "7b67a2115e7a0f82884335689329ca90", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:7b67a2115e7a0f82884335689329ca90:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637172189717", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637172189717", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "4b50e6d67aefce5c9b3e0334924144f2", "title": "AI Capable Java Engineer", "employer_name": "Citigroup Inc.", "employer_slug": "citigroup", "location_text": "PUNE, Mahārāshtra, India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://citi.eightfold.ai/careers/job/859034416330", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Capable Java Engineer PUNE, Mahārāshtra, India", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.0894ff4318dd6a6bc5", "query_id": "gq_95345352ba55a57d7917", "job_id": "4b50e6d67aefce5c9b3e0334924144f2", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4b50e6d67aefce5c9b3e0334924144f2:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034416330", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034416330", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "68b6bcbdeaa9213a4cab774b8dc99817", "title": "Senior Gen AI Engineer", "employer_name": "DXC Technology", "employer_slug": "dxc-technology", "location_text": "IND - TN - CHENNAI", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-25T00:00:00.000Z", "apply_url": "https://dxctechnology.wd1.myworkdayjobs.com/DXCJobs/job/IND---TN---CHENNAI/AI-ML-Engineer_51579275", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Gen AI Engineer IND - TN - CHENNAI posted: Posted 18 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1688568/000168856826000022/dxc-20260331.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1688568/000168856826000022/dxc-20260331.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.19b456a934510a2c32", "query_id": "gq_95345352ba55a57d7917", "job_id": "68b6bcbdeaa9213a4cab774b8dc99817", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:68b6bcbdeaa9213a4cab774b8dc99817:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1688568/000168856826000022/dxc-20260331.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1688568/000168856826000022/dxc-20260331.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://dxctechnology.wd1.myworkdayjobs.com/DXCJobs/job/IND---TN---CHENNAI/AI-ML-Engineer_51579275", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://dxctechnology.wd1.myworkdayjobs.com/DXCJobs/job/IND---TN---CHENNAI/AI-ML-Engineer_51579275", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "f8d50ff792a24484d0eb4949d80e0151", "title": "Machine Learning Engineer", "employer_name": "Magna International Inc.", "employer_slug": "magna-international", "location_text": "2 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-08T00:00:00.000Z", "apply_url": "https://magna.wd3.myworkdayjobs.com/Magna/job/Timisoara-RO/Machine-Learning-Engineer_R00172354", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer 2 Locations posted: Posted 4 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.638cdefefe0a3c0d63", "query_id": "gq_95345352ba55a57d7917", "job_id": "f8d50ff792a24484d0eb4949d80e0151", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f8d50ff792a24484d0eb4949d80e0151:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://magna.wd3.myworkdayjobs.com/Magna/job/Timisoara-RO/Machine-Learning-Engineer_R00172354", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://magna.wd3.myworkdayjobs.com/Magna/job/Timisoara-RO/Machine-Learning-Engineer_R00172354", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "9a0631f0c31f405762dc0c3e524e2bd2", "title": "Senior Applied Researcher, AI Agentic Systems", "employer_name": "NVIDIA Corporation", "employer_slug": "nvidia", "location_text": "Israel, Tel Aviv", "country": "IL", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-Applied-Researcher--AI-Agentic-Systems_JR2016502", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Applied Researcher, AI Agentic Systems Israel, Tel Aviv posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c16a1767887b7dd386", "query_id": "gq_95345352ba55a57d7917", "job_id": "9a0631f0c31f405762dc0c3e524e2bd2", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9a0631f0c31f405762dc0c3e524e2bd2:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-Applied-Researcher--AI-Agentic-Systems_JR2016502", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-Applied-Researcher--AI-Agentic-Systems_JR2016502", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "0d23a5d9a26309b4548ed82246120b2b", "title": "AI Engineer (Remote, IND)", "employer_name": "CrowdStrike", "employer_slug": "crowdstrike", "location_text": "India - Remote", "country": "IN", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T00:00:00.000Z", "apply_url": "https://crowdstrike.wd5.myworkdayjobs.com/crowdstrikecareers/job/India---Remote/AI-Engineer--Remote--IND-_R28983", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer (Remote, IND) India - Remote posted: Posted Today", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 48, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1535527/000153552726000010/crwd-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1535527/000153552726000010/crwd-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.9c05a4c8173705af03", "query_id": "gq_95345352ba55a57d7917", "job_id": "0d23a5d9a26309b4548ed82246120b2b", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0d23a5d9a26309b4548ed82246120b2b:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://crowdstrike.wd5.myworkdayjobs.com/crowdstrikecareers/job/India---Remote/AI-Engineer--Remote--IND-_R28983", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1535527/000153552726000010/crwd-20260131.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1535527/000153552726000010/crwd-20260131.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://crowdstrike.wd5.myworkdayjobs.com/crowdstrikecareers/job/India---Remote/AI-Engineer--Remote--IND-_R28983", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://crowdstrike.wd5.myworkdayjobs.com/crowdstrikecareers/job/India---Remote/AI-Engineer--Remote--IND-_R28983", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "b8fbfe196169d9d4e3ae64e7950aa391", "title": "Strategic Business Development Representative - EMEA", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Dublin, Ireland, Dublin, Leinster, Ireland", "country": "IE", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-03-30T20:14:58.473Z", "apply_url": "https://jobs.ashbyhq.com/openai/d29b455a-9fee-4610-8e08-ce6a9ea8a37e", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Strategic Business Development Representative - EMEA Dublin, Ireland, Dublin, Leinster, Ireland About the Team OpenAI's Enterprise Go-To-Market organization helps the world's largest companies adopt and scale our AI platform across their business, from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Business Development sits at the front of this motion, where technical curiosity turns into executive engagement, and early product signals become enterprise-wide deployments. About the Role This role is designed as a launchpad for future sellers at OpenAI. This is a highly strategic role with significant exposure to enterprise sales, product, and customer strategy. You'll develop core skills in discovery, stakeholder mapping, deal shaping, and executive communication while building a deep understanding of how leading companies adopt AI. We are looking for individuals with 4-6+ years of professional experience who are motivated to grow into world-class enterprise sellers over time. While many individuals in this role go on to become Account Directors or take on broader GTM roles, progression is based on performance and business needs rather than a fixed timeline. For the right person, this is one of the most accelerated paths to break into sales at OpenAI and build a long-term career in AI go-to-market.", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 4, "years_experience_max": 8, "role_function": "sales", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.64d40726137278e785", "query_id": "gq_95345352ba55a57d7917", "job_id": "b8fbfe196169d9d4e3ae64e7950aa391", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Strategic Business Development Representative - EMEA Dublin, Ireland, Dublin, Leinster, Ireland About the Team OpenAI's Enterprise Go-To-Market organization helps the world's largest companies adopt and scale our AI platform across their business, from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Business Development sits at the front of this motion, where technical curiosity turns into executive engagement, and early product signals become enterprise-wide deployments. About the Role This role is designed as a launchpad for future sellers at OpenAI. This is a highly strategic role with significant exposure to enterprise sales, product, and customer strategy. You'll develop core skills in discovery, stakeholder mapping, deal shaping, and executive communication while building a deep understanding of how leading companies adopt AI. We are looking for individuals with 4-6+ years of professional experience who are motivated to grow into world-class enterprise sellers over time. While many individuals in this role go on to become Account Directors or take on broader GTM roles, progression is based on performance and business needs rather than a fixed timeline. For the right person, this is one of the most accelerated paths to break into sales at OpenAI and build a long-term career in AI go-to-market.", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b8fbfe196169d9d4e3ae64e7950aa391:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.88483d60051efc1299", "query_id": "gq_95345352ba55a57d7917", "job_id": "b8fbfe196169d9d4e3ae64e7950aa391", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b8fbfe196169d9d4e3ae64e7950aa391:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a013ea88ad98c88265", "query_id": "gq_95345352ba55a57d7917", "job_id": "b8fbfe196169d9d4e3ae64e7950aa391", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d29b455a-9fee-4610-8e08-ce6a9ea8a37e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d29b455a-9fee-4610-8e08-ce6a9ea8a37e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "1a47df1ec92e118fb42fb810884e5ad2", "title": "Machine Learning Engineer, Intelligent Sensing Technology - Incubation", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Cupertino, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 147400, "salary_max": 272100, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 147400, "base_salary_max": 272100, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-04-17T22:24:25.373Z", "apply_url": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer, Intelligent Sensing Technology - Incubation Cupertino, United States of America Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring curiosity, passion, and dedication to your job and there's no telling what you could accomplish! Our Camera Incubation team is a multi-disciplinary team responsible for looking down the road and prototyping new experiences, architectures and technologies. We collaborate with design and product teams to bring new features across the Apple product line. Join us as together we explore concept prototypes, helping shape what intelligent cameras can sense, understand, and do-and the experience they create for the people who use them. We're looking for a creative ML Research Engineer to join our incubation team, where you'll work across the full stack, from model training and systems integration to rapid prototyping. While working on a diverse portfolio of exploratory projects, you'll bring deep practical knowledge of ML/AI architectures and multimodal sensing applied to physical spaces, paired with a design-centric approach to moving ideas from experiment to integrated system. The ideal candidate is energized by open questions, comfortable navigating ambiguity, quick to reorient when new data shifts the direction, and always able to clearly articulate the motivation, tradeoffs, and risks behind their approach. Minimum Qualifications: BS and a minimum of 3 years relevant industry experience in machine learning or AI engineering Familiarity with state-of-the-art architectures including transformers, reinforcement learning, and predictive inference Strong coding skills across", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.5ff585ce95a1c018e2", "query_id": "gq_95345352ba55a57d7917", "job_id": "1a47df1ec92e118fb42fb810884e5ad2", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:1a47df1ec92e118fb42fb810884e5ad2:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657302/machine-learning-engineer-intelligent-sensing-technology-incubation?team=HRDWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "bc88b6bcfc214d0be75be4bb9ea48022", "title": "Solutions Engineering, Ads Solutions", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-02T01:12:51.965Z", "apply_url": "https://jobs.ashbyhq.com/openai/9f179118-5df6-4ccb-b8d1-cfb0642fba37", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Solutions Engineering, Ads Solutions San Francisco, California, United States About the Team OpenAI's mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Ads Solutions team partners closely with advertisers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform-while maintaining strong standards for user trust and platform integrity. About the Role We're looking for an Ads Solutions Engineer to partner with advertisers and agencies throughout the pre-sales and growth lifecycle, helping them successfully evaluate, launch, and scale on OpenAI's advertising platform. You will serve as the technical expert in the sales process, translating advertiser objectives into scalable technical solutions across measurement, integrations, data activation, and campaign execution. This role sits at the intersection of sales, product, and engineering. You'll work closely with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams to remove technical blockers, accelerate revenue growth, and shape the future of OpenAI's ads platform. In this role, you will: - Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure. - Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals. - Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks. - Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.c4c4a1d273ef54ed39", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc88b6bcfc214d0be75be4bb9ea48022", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Solutions Engineering, Ads Solutions San Francisco, California, United States About the Team OpenAI's mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Ads Solutions team partners closely with advertisers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform-while maintaining strong standards for user trust and platform integrity. About the Role We're looking for an Ads Solutions Engineer to partner with advertisers and agencies throughout the pre-sales and growth lifecycle, helping them successfully evaluate, launch, and scale on OpenAI's advertising platform. You will serve as the technical expert in the sales process, translating advertiser objectives into scalable technical solutions across measurement, integrations, data activation, and campaign execution. This role sits at the intersection of sales, product, and engineering. You'll work closely with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams to remove technical blockers, accelerate revenue growth, and shape the future of OpenAI's ads platform. In this role, you will: - Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure. - Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals. - Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks. - Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:bc88b6bcfc214d0be75be4bb9ea48022:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.d29178141ebcad5319", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc88b6bcfc214d0be75be4bb9ea48022", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:bc88b6bcfc214d0be75be4bb9ea48022:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.27d1536a4a3232a33d", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc88b6bcfc214d0be75be4bb9ea48022", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/9f179118-5df6-4ccb-b8d1-cfb0642fba37", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/9f179118-5df6-4ccb-b8d1-cfb0642fba37", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "8d11cf5daf99298b3abf4bd99b72f7b9", "title": "AI Developer Evangelist", "employer_name": "Intel", "employer_slug": "intel", "location_text": "3 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T00:00:00.000Z", "apply_url": "https://intel.wd1.myworkdayjobs.com/External/job/US-Oregon-Hillsboro/AI-Developer-Evangelist_JR0284330", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Developer Evangelist 3 Locations posted: Posted 2 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/50863/000005086326000011/intc-20251227.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/50863/000005086326000011/intc-20251227.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.de188399f3b0dce073", "query_id": "gq_95345352ba55a57d7917", "job_id": "8d11cf5daf99298b3abf4bd99b72f7b9", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:8d11cf5daf99298b3abf4bd99b72f7b9:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/50863/000005086326000011/intc-20251227.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/50863/000005086326000011/intc-20251227.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://intel.wd1.myworkdayjobs.com/External/job/US-Oregon-Hillsboro/AI-Developer-Evangelist_JR0284330", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://intel.wd1.myworkdayjobs.com/External/job/US-Oregon-Hillsboro/AI-Developer-Evangelist_JR0284330", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "c1eda52968d4e0082eb8984357052bfa", "title": "Senior Manager, Technical Accounting (Compute Infrastructure)", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 216000, "salary_max": 240000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 216000, "base_salary_max": 240000, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-08T22:56:02.813Z", "apply_url": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Manager, Technical Accounting (Compute Infrastructure) San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Technical Accounting team plays a crucial role in helping OpenAI navigate complex, judgmental, and rapidly evolving accounting matters with rigor and clarity. We aim to bring both technical excellence and strong business partnership to some of the most novel accounting questions in the industry. About the Role As a Technical Accounting Manager, Compute Infrastructure, you will lead the evaluation, documentation, and operationalization of complex accounting matters related to OpenAI's compute infrastructure and other strategic business activities. This is a high-impact role at the intersection of technical accounting, infrastructure strategy, financial reporting, and cross-functional execution. You will be responsible for analyzing complex and non-routine transactions under U.S. GAAP, developing well-supported accounting conclusions, and translating those conclusions into practical guidance for accounting operations, financial reporting, controls, and business partners. Areas of focus may include leases, cloud compute arrangements, power purchase agreements, related strategic investments, consolidation evaluations, and other emerging or non-standard arrangements. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Evaluate complex, judgmental, and non-routine transactions and document accounting conclusions under U.S. GAAP. - Partner with Controllership, Tax, Legal, FP&A, Procurement, Infrastructure, and other cross-functional teams to assess the accounting implications of", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.39c0cb3de416abd981", "query_id": "gq_95345352ba55a57d7917", "job_id": "c1eda52968d4e0082eb8984357052bfa", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Manager, Technical Accounting (Compute Infrastructure) San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Technical Accounting team plays a crucial role in helping OpenAI navigate complex, judgmental, and rapidly evolving accounting matters with rigor and clarity. We aim to bring both technical excellence and strong business partnership to some of the most novel accounting questions in the industry. About the Role As a Technical Accounting Manager, Compute Infrastructure, you will lead the evaluation, documentation, and operationalization of complex accounting matters related to OpenAI's compute infrastructure and other strategic business activities. This is a high-impact role at the intersection of technical accounting, infrastructure strategy, financial reporting, and cross-functional execution. You will be responsible for analyzing complex and non-routine transactions under U.S. GAAP, developing well-supported accounting conclusions, and translating those conclusions into practical guidance for accounting operations, financial reporting, controls, and business partners. Areas of focus may include leases, cloud compute arrangements, power purchase agreements, related strategic investments, consolidation evaluations, and other emerging or non-standard arrangements. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Evaluate complex, judgmental, and non-routine transactions and document accounting conclusions under U.S. GAAP. - Partner with Controllership, Tax, Legal, FP&A, Procurement, Infrastructure, and other cross-functional teams to assess the accounting implications of", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c1eda52968d4e0082eb8984357052bfa:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.abe3e16a1bfbf1364e", "query_id": "gq_95345352ba55a57d7917", "job_id": "c1eda52968d4e0082eb8984357052bfa", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c1eda52968d4e0082eb8984357052bfa:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.bbe50ca5d731b5d39c", "query_id": "gq_95345352ba55a57d7917", "job_id": "c1eda52968d4e0082eb8984357052bfa", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/5c85c498-6459-4e4a-937c-6bc9150f743e", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "c4d24032b3c5036300a337938f357516", "title": "Senior Staff Software Engineer, Identity Infrastructure Engineering", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-02T21:01:11.222Z", "apply_url": "https://jobs.ashbyhq.com/openai/72a58872-70e2-4340-a259-e9bea3596883", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Staff Software Engineer, Identity Infrastructure Engineering San Francisco, California, United States About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI-Applied Engineering, Research, IT, and Security-to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. About the Role We're looking for a Staff+ Software Engineer to help build and evolve the identity infrastructure that supports OpenAI's research, engineering, and internal platforms. This role sits at the intersection of cloud infrastructure, identity systems, and software engineering. You'll work across production systems, infrastructure-as-code, cloud control planes, identity providers, and operational infrastructure to build secure, scalable, and reliable systems used broadly across the company. The ideal candidate has experience building and operating large-scale, mission-critical systems with strong reliability and security requirements, and is comfortable writing production code, designing distributed systems, and driving ambiguous projects from 0 to 1 while building the operational rigor needed to run critical infrastructure over time. In this role, you will: - Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services. - Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "security_clearance": { "field": "security_clearance", "source": "llm:greenfield:inv_371_postfix", "db_column": "security_clearance" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "secret", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b2088307a62a42e1bf", "query_id": "gq_95345352ba55a57d7917", "job_id": "c4d24032b3c5036300a337938f357516", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Staff Software Engineer, Identity Infrastructure Engineering San Francisco, California, United States About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI-Applied Engineering, Research, IT, and Security-to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. About the Role We're looking for a Staff+ Software Engineer to help build and evolve the identity infrastructure that supports OpenAI's research, engineering, and internal platforms. This role sits at the intersection of cloud infrastructure, identity systems, and software engineering. You'll work across production systems, infrastructure-as-code, cloud control planes, identity providers, and operational infrastructure to build secure, scalable, and reliable systems used broadly across the company. The ideal candidate has experience building and operating large-scale, mission-critical systems with strong reliability and security requirements, and is comfortable writing production code, designing distributed systems, and driving ambiguous projects from 0 to 1 while building the operational rigor needed to run critical infrastructure over time. In this role, you will: - Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services. - Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c4d24032b3c5036300a337938f357516:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.3107abbf0bed3a417d", "query_id": "gq_95345352ba55a57d7917", "job_id": "c4d24032b3c5036300a337938f357516", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c4d24032b3c5036300a337938f357516:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.d0fa792a4637dcaac5", "query_id": "gq_95345352ba55a57d7917", "job_id": "c4d24032b3c5036300a337938f357516", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/72a58872-70e2-4340-a259-e9bea3596883", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/72a58872-70e2-4340-a259-e9bea3596883", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4726baf3b54b1e27a669b1b83610bd60", "title": "Applied AI, Forward Deployed Machine Learning Engineer - Montreal", "employer_name": "Mistral AI", "employer_slug": "mistral-ai", "location_text": "Montreal", "country": "CA", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "CAD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn", "a16z", "generalcatalyst" ], "posted_at": "2026-03-21T01:37:59.776Z", "apply_url": "https://jobs.lever.co/mistral/a73cb128-b07e-437c-b82d-57b06661c52b", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI, Forward Deployed Machine Learning Engineer - Montreal Montreal About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations. In this role, you'll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers)", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": 6, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.aa40cd09e89f10edd2", "query_id": "gq_95345352ba55a57d7917", "job_id": "4726baf3b54b1e27a669b1b83610bd60", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4726baf3b54b1e27a669b1b83610bd60:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/mistral/a73cb128-b07e-437c-b82d-57b06661c52b", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/mistral/a73cb128-b07e-437c-b82d-57b06661c52b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/mistral/a73cb128-b07e-437c-b82d-57b06661c52b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "c5d26f6953bd5786dd7bd753eefc047b", "title": "Data Scientist, Safety", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, New York City", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 230000, "salary_max": 325000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 230000, "base_salary_max": 325000, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-15T23:36:37.483Z", "apply_url": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Scientist, Safety San Francisco, California, United States, New York City About the Team OpenAI's Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company's most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: - Measure harmful or abusive behavior across OpenAI's products - Detect fraud, manipulation, coordinated misuse - Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows - Design experiments and causal analyses to understand product, policy, and mitigation impacts - Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks - Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs - Translate ambiguous safety risks into measurable problems and evidence-based recommendations - Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes - Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We're looking for strong Data Scientists who thrive", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b169f9ef994a6f7263", "query_id": "gq_95345352ba55a57d7917", "job_id": "c5d26f6953bd5786dd7bd753eefc047b", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Data Scientist, Safety San Francisco, California, United States, New York City About the Team OpenAI's Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company's most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: - Measure harmful or abusive behavior across OpenAI's products - Detect fraud, manipulation, coordinated misuse - Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows - Design experiments and causal analyses to understand product, policy, and mitigation impacts - Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks - Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs - Translate ambiguous safety risks into measurable problems and evidence-based recommendations - Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes - Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We're looking for strong Data Scientists who thrive", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c5d26f6953bd5786dd7bd753eefc047b:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4cc5af4ab4e4665035", "query_id": "gq_95345352ba55a57d7917", "job_id": "c5d26f6953bd5786dd7bd753eefc047b", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c5d26f6953bd5786dd7bd753eefc047b:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.6c945aaa85ce7b687f", "query_id": "gq_95345352ba55a57d7917", "job_id": "c5d26f6953bd5786dd7bd753eefc047b", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/90c711dc-5f50-46e3-a5ab-82359a56d683", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "043a740c0e33d89fd4254f9b7c7d5d79", "title": "Performance Modeling Engineer ~2", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, Seattle", "country": "US", "employment_type": "internship", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-20T19:33:18.325Z", "apply_url": "https://jobs.ashbyhq.com/openai/4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Performance Modeling Engineer ~2 San Francisco, California, United States, Seattle About the Team OpenAI's Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1-2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Support the development and maintenance of performance modeling tools and frameworks - Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems - Help analyze distributed system scaling behavior and identify performance bottlenecks", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 1, "years_experience_max": 6, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.0fb87a98f3757c7bee", "query_id": "gq_95345352ba55a57d7917", "job_id": "043a740c0e33d89fd4254f9b7c7d5d79", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.7508a6b540e056c542", "query_id": "gq_95345352ba55a57d7917", "job_id": "043a740c0e33d89fd4254f9b7c7d5d79", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:043a740c0e33d89fd4254f9b7c7d5d79:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "a09fcb803a97a42e6a0a4b9c0277849b", "title": "Agentic AI Engineer", "employer_name": "Rimini Street Inc", "employer_slug": "rimini-street", "location_text": "Hyderabad", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://riministreet.wd1.myworkdayjobs.com/RiminiStreet/job/Hyderabad/Agentic-AI-Engineer_R-102058", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Agentic AI Engineer Hyderabad posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1635282/000163528226000014/rmni-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1635282/000163528226000014/rmni-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.862f921a84c5e33200", "query_id": "gq_95345352ba55a57d7917", "job_id": "a09fcb803a97a42e6a0a4b9c0277849b", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:a09fcb803a97a42e6a0a4b9c0277849b:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1635282/000163528226000014/rmni-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1635282/000163528226000014/rmni-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://riministreet.wd1.myworkdayjobs.com/RiminiStreet/job/Hyderabad/Agentic-AI-Engineer_R-102058", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://riministreet.wd1.myworkdayjobs.com/RiminiStreet/job/Hyderabad/Agentic-AI-Engineer_R-102058", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "4aa97308ff0a58574e68d67961734ac7", "title": "Lead AI Engineer", "employer_name": "Marsh McLennan", "employer_slug": "marsh-mclennan", "location_text": "Dublin - Charlotte", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-02T00:00:00.000Z", "apply_url": "https://mmc.wd1.myworkdayjobs.com/MMC/job/Dublin---Charlotte/Lead-AI-Engineer_R_352757", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Lead AI Engineer Dublin - Charlotte posted: Posted 10 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/62709/000006270926000022/mrsh-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/62709/000006270926000022/mrsh-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.57b2c25be24dcefb6d", "query_id": "gq_95345352ba55a57d7917", "job_id": "4aa97308ff0a58574e68d67961734ac7", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4aa97308ff0a58574e68d67961734ac7:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/62709/000006270926000022/mrsh-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/62709/000006270926000022/mrsh-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://mmc.wd1.myworkdayjobs.com/MMC/job/Dublin---Charlotte/Lead-AI-Engineer_R_352757", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://mmc.wd1.myworkdayjobs.com/MMC/job/Dublin---Charlotte/Lead-AI-Engineer_R_352757", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "3cd1b85b9da42431b293486b74efd121", "title": "Senior Generative AI Engineer - Vice President", "employer_name": "Citigroup Inc.", "employer_slug": "citigroup", "location_text": "CHENNAI, Tamil Nādu, India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://citi.eightfold.ai/careers/job/859034703679", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Generative AI Engineer - Vice President CHENNAI, Tamil Nādu, India", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.53a63a6fbb7bc28e5e", "query_id": "gq_95345352ba55a57d7917", "job_id": "3cd1b85b9da42431b293486b74efd121", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:3cd1b85b9da42431b293486b74efd121:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034703679", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034703679", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "d02bda6ededa6ce8c78774b509b82758", "title": "Industrial Builds, Senior Project Manager, Design and Construction", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-03-13T01:01:49.815Z", "apply_url": "https://jobs.ashbyhq.com/openai/806ddc92-8b5b-4339-a830-eb4378b4e146", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Industrial Builds, Senior Project Manager, Design and Construction San Francisco, California, United States About the Team The Real Estate team at OpenAI is responsible for delivering workplaces that exist at the intersection of operational excellence and elevated aesthetics, and managing OpenAI's real estate portfolio to ensure that the organization is well-positioned for success in pursuit of our mission. About the Role As an Industrial Builds Project Manager on the Design & Construction team, you will support OpenAI's research, scaling and manufacturing activities by providing project management and leadership on mission critical construction projects with complex engineering design and extensive interfaces. This role owns technical coordination across MEP, civil/structural, and architectural scopes, and is accountable for on-time, on-budget delivery of complex build-outs. This role is based in San Francisco, CA, but you will be expected to travel to project sites regularly, aligned with project requirements. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Lead full lifecycle execution of a range of infrastructure and facilities build-out projects simultaneously, including advanced compute facilities, labs, testing environments, and production spaces. - Own detailed project estimating, budgeting, and financial analysis to ensure fiscal responsibility and efficiency. This includes securing capital funding - Engage, contract and drive external partners (architects, contractors, construction managers and other consultants) to deliver mission-critical projects on accelerated timelines - Collaborate closely on projects with internal teams like Real Estate, Operations, Corporate Security,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "operations", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.006f5b2bc5435c3da7", "query_id": "gq_95345352ba55a57d7917", "job_id": "d02bda6ededa6ce8c78774b509b82758", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Industrial Builds, Senior Project Manager, Design and Construction San Francisco, California, United States About the Team The Real Estate team at OpenAI is responsible for delivering workplaces that exist at the intersection of operational excellence and elevated aesthetics, and managing OpenAI's real estate portfolio to ensure that the organization is well-positioned for success in pursuit of our mission. About the Role As an Industrial Builds Project Manager on the Design & Construction team, you will support OpenAI's research, scaling and manufacturing activities by providing project management and leadership on mission critical construction projects with complex engineering design and extensive interfaces. This role owns technical coordination across MEP, civil/structural, and architectural scopes, and is accountable for on-time, on-budget delivery of complex build-outs. This role is based in San Francisco, CA, but you will be expected to travel to project sites regularly, aligned with project requirements. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Lead full lifecycle execution of a range of infrastructure and facilities build-out projects simultaneously, including advanced compute facilities, labs, testing environments, and production spaces. - Own detailed project estimating, budgeting, and financial analysis to ensure fiscal responsibility and efficiency. This includes securing capital funding - Engage, contract and drive external partners (architects, contractors, construction managers and other consultants) to deliver mission-critical projects on accelerated timelines - Collaborate closely on projects with internal teams like Real Estate, Operations, Corporate Security,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d02bda6ededa6ce8c78774b509b82758:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.57dbf759651d6bb6c9", "query_id": "gq_95345352ba55a57d7917", "job_id": "d02bda6ededa6ce8c78774b509b82758", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d02bda6ededa6ce8c78774b509b82758:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4c87abd4d182002a7c", "query_id": "gq_95345352ba55a57d7917", "job_id": "d02bda6ededa6ce8c78774b509b82758", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/806ddc92-8b5b-4339-a830-eb4378b4e146", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/806ddc92-8b5b-4339-a830-eb4378b4e146", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "1f94da0556f1d66f8997769ccbe9781e", "title": "AI Senior Consultant", "employer_name": "Kyndryl", "employer_slug": "kyndryl", "location_text": "Madrid, Spain", "country": "ES", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-25T00:00:00.000Z", "apply_url": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/Madrid-Spain/AI-Senior-Consultant_R-58106", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Senior Consultant Madrid, Spain posted: Posted 18 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.bfd085ce0b38b775c7", "query_id": "gq_95345352ba55a57d7917", "job_id": "1f94da0556f1d66f8997769ccbe9781e", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:1f94da0556f1d66f8997769ccbe9781e:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/Madrid-Spain/AI-Senior-Consultant_R-58106", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/Madrid-Spain/AI-Senior-Consultant_R-58106", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "48515ffd85ae7079a9e9883df24087a4", "title": "AI Tutor - Danish", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Remote", "country": "unknown", "employment_type": "part_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 35, "salary_max": 45, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 35, "base_salary_max": 45, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2026-03-27T09:07:16.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Danish Remote ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor specialized in multilingual audio capabilities, you will contribute to xAI's mission by training and refining Grok to excel in voice interactions, speech recognition, and auditory experiences across diverse languages, accents, and cultural contexts. Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances. RESPONSIBILITIES: - Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages. - Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "portfolio_required": { "field": "portfolio_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "portfolio_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.fe33a2eef68cefd6c8", "query_id": "gq_95345352ba55a57d7917", "job_id": "48515ffd85ae7079a9e9883df24087a4", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "teaching_education", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:48515ffd85ae7079a9e9883df24087a4:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090189007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "9478389ec219ad4374a646e3dc664cdb", "title": "Senior Machine Learning Engineer", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "3 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer 3 Locations posted: Posted 30+ Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.6666b87f493b760d19", "query_id": "gq_95345352ba55a57d7917", "job_id": "9478389ec219ad4374a646e3dc664cdb", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9478389ec219ad4374a646e3dc664cdb:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "d5072abde348461552d486096690c193", "title": "Software Engineer, Payments", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2025-06-20T18:05:41.319Z", "apply_url": "https://jobs.ashbyhq.com/openai/0da75470-7e1e-44c3-90df-6f93cf90b968", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Payments San Francisco, California, United States About the Team The Payments Team is working to make AGI financially sustainable by enabling OpenAI to accept payments across our existing products (ChatGPT, ChatGPT for Teams, API) and supporting future commercial experiences. We own the user-facing payments experience, direct integrations with payment service providers, and other supporting infrastructure that powers checkout and payment flows. Payments works closely with teams across Finance, Legal, Growth, Product, external vendors and more to ensure our payments infrastructure scales with the business and supports evolving commercial goals. About the Role As a Software Engineer on the Payments Team, you will play a pivotal role in shaping the infrastructure that powers OpenAI's financial systems. You'll design and build core payments systems, partner with cross-functional teams to deliver scalable solutions, and ensure that our financial systems support rapid product iteration and global reach. We're looking for people who are pragmatic, collaborative, and energized by the opportunity to build systems that are foundational to OpenAI's long-term mission and sustainability. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Architect, implement and scale core payment infrastructure. - Build robust and extensible financial primitives to enable rapid iteration and support hyper-growth. - Collaborate closely with internal and external stakeholders (e.g. Finance, GTM, Product, etc) to translate business requirements into clean, scalable technical systems. - Demonstrate", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.4364d762fbf93edf78", "query_id": "gq_95345352ba55a57d7917", "job_id": "d5072abde348461552d486096690c193", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Payments San Francisco, California, United States About the Team The Payments Team is working to make AGI financially sustainable by enabling OpenAI to accept payments across our existing products (ChatGPT, ChatGPT for Teams, API) and supporting future commercial experiences. We own the user-facing payments experience, direct integrations with payment service providers, and other supporting infrastructure that powers checkout and payment flows. Payments works closely with teams across Finance, Legal, Growth, Product, external vendors and more to ensure our payments infrastructure scales with the business and supports evolving commercial goals. About the Role As a Software Engineer on the Payments Team, you will play a pivotal role in shaping the infrastructure that powers OpenAI's financial systems. You'll design and build core payments systems, partner with cross-functional teams to deliver scalable solutions, and ensure that our financial systems support rapid product iteration and global reach. We're looking for people who are pragmatic, collaborative, and energized by the opportunity to build systems that are foundational to OpenAI's long-term mission and sustainability. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Architect, implement and scale core payment infrastructure. - Build robust and extensible financial primitives to enable rapid iteration and support hyper-growth. - Collaborate closely with internal and external stakeholders (e.g. Finance, GTM, Product, etc) to translate business requirements into clean, scalable technical systems. - Demonstrate", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d5072abde348461552d486096690c193:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.791d6865d97cef476a", "query_id": "gq_95345352ba55a57d7917", "job_id": "d5072abde348461552d486096690c193", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d5072abde348461552d486096690c193:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.41cebf43fbfc256432", "query_id": "gq_95345352ba55a57d7917", "job_id": "d5072abde348461552d486096690c193", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0da75470-7e1e-44c3-90df-6f93cf90b968", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0da75470-7e1e-44c3-90df-6f93cf90b968", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "d6ad0f9416485eff7ae08349ca1330fd", "title": "Strategy & Operations Lead, B2B Marketing", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 302000, "salary_max": 335000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 302000, "base_salary_max": 335000, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-27T14:29:52.042Z", "apply_url": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Strategy & Operations Lead, B2B Marketing San Francisco, California, United States About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI's products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. The team operates across field marketing, campaigns, customer storytelling, thought leadership, events, lifecycle programs, and executive communications. We partner closely with Sales, Product, Communications, Finance, Recruiting, and company leadership to build programs that drive durable growth across enterprise and business audiences. About the Role As a Strategy & Operations Lead on the B2B Marketing team, you will help shape the operating system for one of OpenAI's fastest-moving and highest-priority marketing functions. You will serve as a trusted partner to B2B Marketing leadership, helping steer strategy, define operating priorities, manage budgets and headcount planning, and build the structures, processes, and communication mechanisms the team needs to scale. This is a lead role for someone who can own ambiguous, high-impact scopes end to end: setting direction, building the plan, aligning stakeholders, driving execution, and shaping how operations works across the B2B Marketing team. You will work closely with Strategic Finance, Recruiting, Marketing leaders, and cross-functional partners to bring clarity to complex problems and keep leadership informed on progress, risks, and tradeoffs. We're looking for someone who is analytical, operationally rigorous, deeply familiar with how marketing teams operate, and comfortable influencing senior stakeholders without formal authority. You'll be responsible", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 14, "years_experience_max": 15, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ff392f6651d372475e", "query_id": "gq_95345352ba55a57d7917", "job_id": "d6ad0f9416485eff7ae08349ca1330fd", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Strategy & Operations Lead, B2B Marketing San Francisco, California, United States About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI's products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. The team operates across field marketing, campaigns, customer storytelling, thought leadership, events, lifecycle programs, and executive communications. We partner closely with Sales, Product, Communications, Finance, Recruiting, and company leadership to build programs that drive durable growth across enterprise and business audiences. About the Role As a Strategy & Operations Lead on the B2B Marketing team, you will help shape the operating system for one of OpenAI's fastest-moving and highest-priority marketing functions. You will serve as a trusted partner to B2B Marketing leadership, helping steer strategy, define operating priorities, manage budgets and headcount planning, and build the structures, processes, and communication mechanisms the team needs to scale. This is a lead role for someone who can own ambiguous, high-impact scopes end to end: setting direction, building the plan, aligning stakeholders, driving execution, and shaping how operations works across the B2B Marketing team. You will work closely with Strategic Finance, Recruiting, Marketing leaders, and cross-functional partners to bring clarity to complex problems and keep leadership informed on progress, risks, and tradeoffs. We're looking for someone who is analytical, operationally rigorous, deeply familiar with how marketing teams operate, and comfortable influencing senior stakeholders without formal authority. You'll be responsible", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d6ad0f9416485eff7ae08349ca1330fd:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.21728d883bd59a8ed4", "query_id": "gq_95345352ba55a57d7917", "job_id": "d6ad0f9416485eff7ae08349ca1330fd", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d6ad0f9416485eff7ae08349ca1330fd:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.283a94e6fb45631c9a", "query_id": "gq_95345352ba55a57d7917", "job_id": "d6ad0f9416485eff7ae08349ca1330fd", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/493f5328-27bc-4987-9cc1-47ec3793a4d5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "e3e88a147ba05ad4b57007cd56ac958d", "title": "Senior AI Engineer", "employer_name": "Morgan Stanley", "employer_slug": "morgan-stanley", "location_text": "New York, New York, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://ms.wd5.myworkdayjobs.com/External/job/New-York-New-York-United-States-of-America/Senior-AI-Engineer_PT-JR036109", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Engineer New York, New York, United States of America posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/895421/000089542126000086/ms-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/895421/000089542126000086/ms-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.f71f0dd7843bc4b2d3", "query_id": "gq_95345352ba55a57d7917", "job_id": "e3e88a147ba05ad4b57007cd56ac958d", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:e3e88a147ba05ad4b57007cd56ac958d:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/895421/000089542126000086/ms-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/895421/000089542126000086/ms-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://ms.wd5.myworkdayjobs.com/External/job/New-York-New-York-United-States-of-America/Senior-AI-Engineer_PT-JR036109", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://ms.wd5.myworkdayjobs.com/External/job/New-York-New-York-United-States-of-America/Senior-AI-Engineer_PT-JR036109", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "ecf88e2ab95c6b92434ec67b4fc6cf58", "title": "Data Scientist, Strategic Finance", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2025-10-21T21:16:55.178Z", "apply_url": "https://jobs.ashbyhq.com/openai/71655236-0303-42aa-9135-b2f27f2457ab", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Scientist, Strategic Finance San Francisco, California, United States About the Team The Strategic Finance team is responsible for some of the largest investment categories at OpenAI. We play a critical role in maximizing OpenAI's long-term value by partnering across the business to allocate and deploy resources for the highest-impact outcomes. We work cross-functionally with Finance, Product, Engineering, and Go-To-Market teams to deliver actionable insights and support strategic decision-making. About the Role As one of the founding Data Scientists on the Strategic Finance Data Science team, you will design, implement, and own critical models, reporting, and analysis. You will work closely with Finance leadership, as well as teams across Research, Applied and Go-To-Market. This role requires deep expertise in predictive modeling, causal inference, and the ability to surface insights to support high-stakes decision-making. This role is based in our San Francisco HQ. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: - Become an expert in OpenAI's data and systems. Partnering with Data Engineering, Finance, and other teams, you'll self-serve data to derive critical insights. - Scale causal inference models to measure the impact of different actions on user growth and financial outcomes. - Architect customer segmentation frameworks to unlock tailored growth strategies and expand lifetime value. - Automate standardized reporting and analysis by building data products or agentic solutions. - Support product pricing and other business decisions with ad hoc analysis. -", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 10, "years_experience_max": 14, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.64e3a9c30c66a4e24d", "query_id": "gq_95345352ba55a57d7917", "job_id": "ecf88e2ab95c6b92434ec67b4fc6cf58", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Data Scientist, Strategic Finance San Francisco, California, United States About the Team The Strategic Finance team is responsible for some of the largest investment categories at OpenAI. We play a critical role in maximizing OpenAI's long-term value by partnering across the business to allocate and deploy resources for the highest-impact outcomes. We work cross-functionally with Finance, Product, Engineering, and Go-To-Market teams to deliver actionable insights and support strategic decision-making. About the Role As one of the founding Data Scientists on the Strategic Finance Data Science team, you will design, implement, and own critical models, reporting, and analysis. You will work closely with Finance leadership, as well as teams across Research, Applied and Go-To-Market. This role requires deep expertise in predictive modeling, causal inference, and the ability to surface insights to support high-stakes decision-making. This role is based in our San Francisco HQ. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: - Become an expert in OpenAI's data and systems. Partnering with Data Engineering, Finance, and other teams, you'll self-serve data to derive critical insights. - Scale causal inference models to measure the impact of different actions on user growth and financial outcomes. - Architect customer segmentation frameworks to unlock tailored growth strategies and expand lifetime value. - Automate standardized reporting and analysis by building data products or agentic solutions. - Support product pricing and other business decisions with ad hoc analysis. -", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:ecf88e2ab95c6b92434ec67b4fc6cf58:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.73d01ad6cbe9c68f06", "query_id": "gq_95345352ba55a57d7917", "job_id": "ecf88e2ab95c6b92434ec67b4fc6cf58", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:ecf88e2ab95c6b92434ec67b4fc6cf58:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a878f6441ce0577783", "query_id": "gq_95345352ba55a57d7917", "job_id": "ecf88e2ab95c6b92434ec67b4fc6cf58", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/71655236-0303-42aa-9135-b2f27f2457ab", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/71655236-0303-42aa-9135-b2f27f2457ab", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f0eef7ed710e5cf3e63a6e5766190455", "title": "Strategic Sales Development Representative - SF", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-03-24T18:49:59.913Z", "apply_url": "https://jobs.ashbyhq.com/openai/55f36629-8351-41d9-b2f5-3d63c5e26bf7", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Strategic Sales Development Representative - SF San Francisco, California, United States About the Team OpenAI's Enterprise Go-To-Market organization helps the world's largest companies adopt and scale our AI platform across their business-from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Sales Development sits at the front of this motion-where technical curiosity turns into executive engagement, and early product signals become enterprise-wide deployments. About the Role This role is designed as a launchpad for future enterprise sellers at OpenAI. This is a highly strategic role with significant exposure to enterprise sales, product, and customer strategy. You'll develop core skills in discovery, stakeholder mapping, deal shaping, and executive communication while building a deep understanding of how leading companies adopt AI. We are looking for individuals with 4-6+ years of professional experience who are motivated to grow into world-class enterprise sellers over time. While many individuals in this role go on to become Account Directors or take on broader GTM roles, progression is based on performance and business needs rather than a fixed timeline. For the right person, this is one of the most accelerated paths to break into sales at OpenAI and build a long-term career in AI go-to-market. In", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 4, "years_experience_max": 8, "role_function": "sales", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2396dbbb7ea0c280c1", "query_id": "gq_95345352ba55a57d7917", "job_id": "f0eef7ed710e5cf3e63a6e5766190455", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Strategic Sales Development Representative - SF San Francisco, California, United States About the Team OpenAI's Enterprise Go-To-Market organization helps the world's largest companies adopt and scale our AI platform across their business-from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Sales Development sits at the front of this motion-where technical curiosity turns into executive engagement, and early product signals become enterprise-wide deployments. About the Role This role is designed as a launchpad for future enterprise sellers at OpenAI. This is a highly strategic role with significant exposure to enterprise sales, product, and customer strategy. You'll develop core skills in discovery, stakeholder mapping, deal shaping, and executive communication while building a deep understanding of how leading companies adopt AI. We are looking for individuals with 4-6+ years of professional experience who are motivated to grow into world-class enterprise sellers over time. While many individuals in this role go on to become Account Directors or take on broader GTM roles, progression is based on performance and business needs rather than a fixed timeline. For the right person, this is one of the most accelerated paths to break into sales at OpenAI and build a long-term career in AI go-to-market. In", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f0eef7ed710e5cf3e63a6e5766190455:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f5867b301c45b05bfe", "query_id": "gq_95345352ba55a57d7917", "job_id": "f0eef7ed710e5cf3e63a6e5766190455", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f0eef7ed710e5cf3e63a6e5766190455:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.1c0c2c4c4ce86980b4", "query_id": "gq_95345352ba55a57d7917", "job_id": "f0eef7ed710e5cf3e63a6e5766190455", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/55f36629-8351-41d9-b2f5-3d63c5e26bf7", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/55f36629-8351-41d9-b2f5-3d63c5e26bf7", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/55f36629-8351-41d9-b2f5-3d63c5e26bf7", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "3845efd2e53739d6da37a177e9dc69ef", "title": "AI Tutor - Gujarati", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Remote", "country": "unknown", "employment_type": "part_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 35, "salary_max": 45, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 35, "base_salary_max": 45, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2026-04-01T04:38:05.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Gujarati Remote ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor specialized in multilingual audio capabilities, you will contribute to xAI's mission by training and refining Grok to excel in voice interactions, speech recognition, and auditory experiences across diverse languages, accents, and cultural contexts. Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances. RESPONSIBILITIES: - Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages. - Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.5761174e1110c99edd", "query_id": "gq_95345352ba55a57d7917", "job_id": "3845efd2e53739d6da37a177e9dc69ef", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "teaching_education", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:3845efd2e53739d6da37a177e9dc69ef:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "rule:remote_status" ], "checked_at": null }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090203007", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "7b7d57a676335e1e6ab9c3aa0c0e0fa4", "title": "AI Engineer", "employer_name": "CACI", "employer_slug": "caci", "location_text": "Remote (Any State)", "country": "unknown", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-05T00:00:00.000Z", "apply_url": "https://caci.wd1.myworkdayjobs.com/External/job/Remote-Any-State/Lead-AI-Engineer_324809", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer Remote (Any State) posted: Posted 7 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 48, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/16058/000162828025038739/caci-20250630.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/16058/000162828025038739/caci-20250630.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.dc84b611f69d224e27", "query_id": "gq_95345352ba55a57d7917", "job_id": "7b7d57a676335e1e6ab9c3aa0c0e0fa4", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:7b7d57a676335e1e6ab9c3aa0c0e0fa4:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://caci.wd1.myworkdayjobs.com/External/job/Remote-Any-State/Lead-AI-Engineer_324809", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/16058/000162828025038739/caci-20250630.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/16058/000162828025038739/caci-20250630.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://caci.wd1.myworkdayjobs.com/External/job/Remote-Any-State/Lead-AI-Engineer_324809", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://caci.wd1.myworkdayjobs.com/External/job/Remote-Any-State/Lead-AI-Engineer_324809", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f29822143a874d8c68d9aa49ece92917", "title": "Associate General Counsel, Executive Compensation & Benefits", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-06T21:01:01.194Z", "apply_url": "https://jobs.ashbyhq.com/openai/cfd44591-1d8a-431c-b082-2b68de4bc736", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Associate General Counsel, Executive Compensation & Benefits San Francisco, California, United States About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI. If you're passionate about doing significant and unique work as a technology lawyer, this team is for you. The team comprises professionals from diverse fields, including technology, AI, privacy, IP, corporate, employment, tax, regulatory, and litigation. About the Role As Associate General Counsel, Executive Compensation & Benefits, you will lead legal support for OpenAI's executive compensation, employee benefits and equity compensation programs. You will partner closely with People, Finance, Equity, Accounting, Tax, Investor Relations and other teams on compensation committee and board matters, global benefits plan design, governance and administration, executive and employee compensation arrangements, disclosure and transaction support, and related processes and controls. This role will report to our Deputy General Counsel, Corporate & Employment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week. In this role, you will: - Advise on a broad range of executive compensation and employee benefits matters, including senior executive, employee, severance, incentive, equity, retention and global benefits arrangements, as well as related plan administration and governance. - Serve as the primary legal advisor for all Compensation Committee matters. - Counsel on equity compensation and employee ownership programs, including equity plan administration, grants, incentive and related programs, securities compliance, and related processes. - Partner closely with cross-functional", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "legal", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.1ccec2ddaf98850654", "query_id": "gq_95345352ba55a57d7917", "job_id": "f29822143a874d8c68d9aa49ece92917", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Associate General Counsel, Executive Compensation & Benefits San Francisco, California, United States About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI. If you're passionate about doing significant and unique work as a technology lawyer, this team is for you. The team comprises professionals from diverse fields, including technology, AI, privacy, IP, corporate, employment, tax, regulatory, and litigation. About the Role As Associate General Counsel, Executive Compensation & Benefits, you will lead legal support for OpenAI's executive compensation, employee benefits and equity compensation programs. You will partner closely with People, Finance, Equity, Accounting, Tax, Investor Relations and other teams on compensation committee and board matters, global benefits plan design, governance and administration, executive and employee compensation arrangements, disclosure and transaction support, and related processes and controls. This role will report to our Deputy General Counsel, Corporate & Employment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week. In this role, you will: - Advise on a broad range of executive compensation and employee benefits matters, including senior executive, employee, severance, incentive, equity, retention and global benefits arrangements, as well as related plan administration and governance. - Serve as the primary legal advisor for all Compensation Committee matters. - Counsel on equity compensation and employee ownership programs, including equity plan administration, grants, incentive and related programs, securities compliance, and related processes. - Partner closely with cross-functional", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f29822143a874d8c68d9aa49ece92917:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.52830a5ce34e301a5f", "query_id": "gq_95345352ba55a57d7917", "job_id": "f29822143a874d8c68d9aa49ece92917", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f29822143a874d8c68d9aa49ece92917:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.ef4ee6fd882e49cbed", "query_id": "gq_95345352ba55a57d7917", "job_id": "f29822143a874d8c68d9aa49ece92917", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/cfd44591-1d8a-431c-b082-2b68de4bc736", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/cfd44591-1d8a-431c-b082-2b68de4bc736", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/cfd44591-1d8a-431c-b082-2b68de4bc736", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f46c48de72a4c33354608d1835d01c93", "title": "Software Engineer, Compute - Storage", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, New York City", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2024-12-10T18:27:47.910Z", "apply_url": "https://jobs.ashbyhq.com/openai/7649205e-20dc-4bb4-9358-69474a851132", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Compute - Storage San Francisco, California, United States, New York City About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI's most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI's research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You'll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: - Build and operate storage services that underpin OpenAI's research infrastructure - Develop object storage systems across cloud and in-house environments - Build systems for cross-region data movement, replication, and recovery - Design lifecycle management capabilities that keep data durable, available, and cost-effective - Evolve the federation layer", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2b9467f3a12c9e3e41", "query_id": "gq_95345352ba55a57d7917", "job_id": "f46c48de72a4c33354608d1835d01c93", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Compute - Storage San Francisco, California, United States, New York City About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI's most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI's research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You'll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: - Build and operate storage services that underpin OpenAI's research infrastructure - Develop object storage systems across cloud and in-house environments - Build systems for cross-region data movement, replication, and recovery - Design lifecycle management capabilities that keep data durable, available, and cost-effective - Evolve the federation layer", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f46c48de72a4c33354608d1835d01c93:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.bf2938080966648f12", "query_id": "gq_95345352ba55a57d7917", "job_id": "f46c48de72a4c33354608d1835d01c93", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f46c48de72a4c33354608d1835d01c93:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.ba0799b15fbf03f430", "query_id": "gq_95345352ba55a57d7917", "job_id": "f46c48de72a4c33354608d1835d01c93", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/7649205e-20dc-4bb4-9358-69474a851132", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/7649205e-20dc-4bb4-9358-69474a851132", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "c3028c2222edfacd89efc2d8cbab5f3f", "title": "Research Scientist - AI Incubation", "employer_name": "Zoom Communications, Inc.", "employer_slug": "zoom-communications", "location_text": "2 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Research-Scientist---AI-Incubation_R18458-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Research Scientist - AI Incubation 2 Locations posted:", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.b1508d4c1ca1321bc0", "query_id": "gq_95345352ba55a57d7917", "job_id": "c3028c2222edfacd89efc2d8cbab5f3f", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:c3028c2222edfacd89efc2d8cbab5f3f:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Research-Scientist---AI-Incubation_R18458-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Research-Scientist---AI-Incubation_R18458-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f70f2444cafb8fc93a1f748d5a441864", "title": "Program Manager - IT Operations", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-27T21:46:44.222Z", "apply_url": "https://jobs.ashbyhq.com/openai/c37587c4-39f3-40e0-b73c-c8bb55a7cd05", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Program Manager - IT Operations San Francisco, California, United States About the Team The Employee Technology & Experience (ETX) team is responsible for delivering a world-class internal technology experience that enables employees to do their best work. We support and operate the employee-facing systems that keep the company moving quickly and efficiently. ETX spans support, logistics, AV, identity, endpoints, SaaS administration, automation, enterprise tooling, and internal infrastructure operations. We partner closely with Security, Engineering, Workplace, Finance, People, and other teams to keep OpenAI's internal technology reliable, scalable, and moving at the pace of the company. About the Role We are hiring a Program Manager to help scale how IT operates across OpenAI. This role will lead complex cross-functional programs that improve operational maturity, streamline how teams work together, and turn high-impact initiatives into durable operational capabilities. You will work across IT, Security, Engineering, Workplace, and other functions to drive alignment, remove friction, and help build the operational foundation needed to support OpenAI's rapid growth. You'll be responsible for: - Lead cross-functional operational programs that improve scalability, consistency, and operational maturity. - Drive operational excellence initiatives across IT Support, employee lifecycle operations, meeting room and calendaring services, onsite support, vending, and research support environments. - Build operating models, readiness plans, escalation paths, governance cadences, and success metrics for complex operational programs. - Partner with technical teams to ensure new deployments, infrastructure investments, and internal platforms are operationally ready and sustainably supported at scale. - Drive high-priority operational programs supporting company growth,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.dda2dfd55826f1e247", "query_id": "gq_95345352ba55a57d7917", "job_id": "f70f2444cafb8fc93a1f748d5a441864", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Program Manager - IT Operations San Francisco, California, United States About the Team The Employee Technology & Experience (ETX) team is responsible for delivering a world-class internal technology experience that enables employees to do their best work. We support and operate the employee-facing systems that keep the company moving quickly and efficiently. ETX spans support, logistics, AV, identity, endpoints, SaaS administration, automation, enterprise tooling, and internal infrastructure operations. We partner closely with Security, Engineering, Workplace, Finance, People, and other teams to keep OpenAI's internal technology reliable, scalable, and moving at the pace of the company. About the Role We are hiring a Program Manager to help scale how IT operates across OpenAI. This role will lead complex cross-functional programs that improve operational maturity, streamline how teams work together, and turn high-impact initiatives into durable operational capabilities. You will work across IT, Security, Engineering, Workplace, and other functions to drive alignment, remove friction, and help build the operational foundation needed to support OpenAI's rapid growth. You'll be responsible for: - Lead cross-functional operational programs that improve scalability, consistency, and operational maturity. - Drive operational excellence initiatives across IT Support, employee lifecycle operations, meeting room and calendaring services, onsite support, vending, and research support environments. - Build operating models, readiness plans, escalation paths, governance cadences, and success metrics for complex operational programs. - Partner with technical teams to ensure new deployments, infrastructure investments, and internal platforms are operationally ready and sustainably supported at scale. - Drive high-priority operational programs supporting company growth,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f70f2444cafb8fc93a1f748d5a441864:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f853e3b98752cfb1da", "query_id": "gq_95345352ba55a57d7917", "job_id": "f70f2444cafb8fc93a1f748d5a441864", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f70f2444cafb8fc93a1f748d5a441864:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.b8041d130cb3d8c8f8", "query_id": "gq_95345352ba55a57d7917", "job_id": "f70f2444cafb8fc93a1f748d5a441864", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c37587c4-39f3-40e0-b73c-c8bb55a7cd05", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c37587c4-39f3-40e0-b73c-c8bb55a7cd05", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "83200813f077e695eb3f3b573c46c336", "title": "Senior Machine Learning Engineer", "employer_name": "GlobalFoundries", "employer_slug": "globalfoundries", "location_text": "IND - Karnataka - Bengaluru - North", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://globalfoundries.wd1.myworkdayjobs.com/External/job/IND---Karnataka---Bengaluru---North/Senior-Machine-Learning-Engineer_JR-2601722", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer IND - Karnataka - Bengaluru - North posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.ae7026381ece8e330e", "query_id": "gq_95345352ba55a57d7917", "job_id": "83200813f077e695eb3f3b573c46c336", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:83200813f077e695eb3f3b573c46c336:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://globalfoundries.wd1.myworkdayjobs.com/External/job/IND---Karnataka---Bengaluru---North/Senior-Machine-Learning-Engineer_JR-2601722", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://globalfoundries.wd1.myworkdayjobs.com/External/job/IND---Karnataka---Bengaluru---North/Senior-Machine-Learning-Engineer_JR-2601722", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f7644461e36cbc58104f0c0c642a297a", "title": "Manager, Technical Revenue Accounting", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-20T21:30:35.642Z", "apply_url": "https://jobs.ashbyhq.com/openai/85333120-a2c2-4bbd-8109-707c896e8bd2", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Manager, Technical Revenue Accounting San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. Our Controllership team provides accurate, timely, and decision-useful financial information to internal and external stakeholders, while building the processes, systems, and controls needed to support a rapidly evolving business. As OpenAI's products, pricing models, and commercial structures continue to expand, we are building a finance organization that can scale with both operational complexity and growth. About the Role As a Technical Revenue Accounting Manager, you will lead high-impact revenue accounting work across complex and evolving commercial arrangements. You will analyze and support accounting conclusions for a broad range of transactions, including subscriptions, usage-based and API arrangements, committed spend structures, contract modifications, multi-product offerings, and other non-standard terms. You will partner with Deal Desk, Legal, Go-to-Market, RevOps, Billing, Product, Strategic Finance, and Revenue Accounting to help OpenAI scale its commercialization efforts while maintaining strong accounting rigor, audit readiness, and operational practicality. This role is critical to ensuring our technical revenue accounting policies, decision frameworks, and processes remain robust as the business grows and changes. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Review complex customer arrangements to identify revenue recognition implications under ASC 606, including non-standard terms, bundled offerings, usage-based pricing, committed spend, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule:title_override", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "finance", "role_function_source": "rule:title_override", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.496f1ac18cfc736507", "query_id": "gq_95345352ba55a57d7917", "job_id": "f7644461e36cbc58104f0c0c642a297a", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Manager, Technical Revenue Accounting San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. Our Controllership team provides accurate, timely, and decision-useful financial information to internal and external stakeholders, while building the processes, systems, and controls needed to support a rapidly evolving business. As OpenAI's products, pricing models, and commercial structures continue to expand, we are building a finance organization that can scale with both operational complexity and growth. About the Role As a Technical Revenue Accounting Manager, you will lead high-impact revenue accounting work across complex and evolving commercial arrangements. You will analyze and support accounting conclusions for a broad range of transactions, including subscriptions, usage-based and API arrangements, committed spend structures, contract modifications, multi-product offerings, and other non-standard terms. You will partner with Deal Desk, Legal, Go-to-Market, RevOps, Billing, Product, Strategic Finance, and Revenue Accounting to help OpenAI scale its commercialization efforts while maintaining strong accounting rigor, audit readiness, and operational practicality. This role is critical to ensuring our technical revenue accounting policies, decision frameworks, and processes remain robust as the business grows and changes. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Review complex customer arrangements to identify revenue recognition implications under ASC 606, including non-standard terms, bundled offerings, usage-based pricing, committed spend, and", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f7644461e36cbc58104f0c0c642a297a:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4b843526fd06ade62a", "query_id": "gq_95345352ba55a57d7917", "job_id": "f7644461e36cbc58104f0c0c642a297a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f7644461e36cbc58104f0c0c642a297a:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4d97dcd456ec07934b", "query_id": "gq_95345352ba55a57d7917", "job_id": "f7644461e36cbc58104f0c0c642a297a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/85333120-a2c2-4bbd-8109-707c896e8bd2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/85333120-a2c2-4bbd-8109-707c896e8bd2", "source_values": [ "rule:title_override" ], "checked_at": null } } }, { "id": "492dbe6ff953ed4d76fb28aaae7ef652", "title": "AI/ML Engineer", "employer_name": "Citigroup Inc.", "employer_slug": "citigroup", "location_text": "CHENNAI, Tamil Nādu, India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://citi.eightfold.ai/careers/job/859035488277", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI/ML Engineer CHENNAI, Tamil Nādu, India", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.8bf496525eed1989c6", "query_id": "gq_95345352ba55a57d7917", "job_id": "492dbe6ff953ed4d76fb28aaae7ef652", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:492dbe6ff953ed4d76fb28aaae7ef652:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859035488277", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859035488277", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "f939d22c42fcd198bff2a224abc7e1a2", "title": "Physical Security Systems Engineer - APAC", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Singapore", "country": "SG", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-01T19:18:23.006Z", "apply_url": "https://jobs.ashbyhq.com/openai/e4d4a64f-1c99-4fde-a0b0-ba86d2440c12", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Physical Security Systems Engineer - APAC Singapore About the Team The Physical Security Engineering team designs, deploys, and sustains the systems that protect OpenAI's people, facilities, and critical infrastructure. We work across global office campuses, warehouses, labs and data centers, partnering with IT, Facilities, Construction, and Security Operations to ensure all environments meet stringent safety, reliability, and compliance requirements. Our team owns security architecture from early site due-diligence through construction, commissioning, and long-term lifecycle management. Role and Responsibilities OpenAI's corporate footprint is expanding quickly across APAC, and our physical security technology needs to scale with the same level of reliability, consistency, and care. The Corporate Security Technology Group owns the access control, video surveillance, and supporting infrastructure that help protect OpenAI's people, offices, and events. This role will be the regional technical owner for designing, operating, troubleshooting, and improving those systems across APAC. This person will partner closely with CorpSec, Workplace/REW, IT/NetEng, and security integrators to bring new offices online, maintain system health, resolve regional escalations, and improve how our physical security systems are documented, supported, and used. We're looking for someone with deep subject matter expertise in Windows OS/Servers, networking and switching, and systems integration support, with the ability to diagnose issues across the full stack from endpoint devices and network infrastructure through servers, databases, and enterprise security platforms. What you'll do - Own day-to-day technical support and administration for physical security systems across APAC, including access control, video management, and related infrastructure. - Support new office buildouts by", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ecfb8ce3f8c7eeb36d", "query_id": "gq_95345352ba55a57d7917", "job_id": "f939d22c42fcd198bff2a224abc7e1a2", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Physical Security Systems Engineer - APAC Singapore About the Team The Physical Security Engineering team designs, deploys, and sustains the systems that protect OpenAI's people, facilities, and critical infrastructure. We work across global office campuses, warehouses, labs and data centers, partnering with IT, Facilities, Construction, and Security Operations to ensure all environments meet stringent safety, reliability, and compliance requirements. Our team owns security architecture from early site due-diligence through construction, commissioning, and long-term lifecycle management. Role and Responsibilities OpenAI's corporate footprint is expanding quickly across APAC, and our physical security technology needs to scale with the same level of reliability, consistency, and care. The Corporate Security Technology Group owns the access control, video surveillance, and supporting infrastructure that help protect OpenAI's people, offices, and events. This role will be the regional technical owner for designing, operating, troubleshooting, and improving those systems across APAC. This person will partner closely with CorpSec, Workplace/REW, IT/NetEng, and security integrators to bring new offices online, maintain system health, resolve regional escalations, and improve how our physical security systems are documented, supported, and used. We're looking for someone with deep subject matter expertise in Windows OS/Servers, networking and switching, and systems integration support, with the ability to diagnose issues across the full stack from endpoint devices and network infrastructure through servers, databases, and enterprise security platforms. What you'll do - Own day-to-day technical support and administration for physical security systems across APAC, including access control, video management, and related infrastructure. - Support new office buildouts by", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f939d22c42fcd198bff2a224abc7e1a2:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.c735b33196038e0d64", "query_id": "gq_95345352ba55a57d7917", "job_id": "f939d22c42fcd198bff2a224abc7e1a2", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f939d22c42fcd198bff2a224abc7e1a2:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5b9e2aa1bd9910687e", "query_id": "gq_95345352ba55a57d7917", "job_id": "f939d22c42fcd198bff2a224abc7e1a2", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/e4d4a64f-1c99-4fde-a0b0-ba86d2440c12", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/e4d4a64f-1c99-4fde-a0b0-ba86d2440c12", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "d89157d0193acb21e1c3c96f914ba71b", "title": "AI Tutor - Tamil", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Remote", "country": "unknown", "employment_type": "part_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 35, "salary_max": 45, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 35, "base_salary_max": 45, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2026-04-01T04:38:21.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Tamil Remote ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor specialized in multilingual audio capabilities, you will contribute to xAI's mission by training and refining Grok to excel in voice interactions, speech recognition, and auditory experiences across diverse languages, accents, and cultural contexts. Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances. RESPONSIBILITIES: - Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages. - Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.bb46a8ebb77eae3349", "query_id": "gq_95345352ba55a57d7917", "job_id": "d89157d0193acb21e1c3c96f914ba71b", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "teaching_education", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d89157d0193acb21e1c3c96f914ba71b:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090269007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "fe1ece3469192982cc42bca636fc01df", "title": "Technical Deployment Lead, Semiconductors", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-08T15:31:55.457Z", "apply_url": "https://jobs.ashbyhq.com/openai/ec9950cb-ccb5-4d2b-b49d-0f6a80b03460", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Deployment Lead, Semiconductors San Francisco, California, United States About the team OpenAI's Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development - working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You'll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You'll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 9, "role_function": "customer_success", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3d12cd3af585bd77a5", "query_id": "gq_95345352ba55a57d7917", "job_id": "fe1ece3469192982cc42bca636fc01df", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Deployment Lead, Semiconductors San Francisco, California, United States About the team OpenAI's Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development - working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You'll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You'll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:fe1ece3469192982cc42bca636fc01df:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.9792372b9299702909", "query_id": "gq_95345352ba55a57d7917", "job_id": "fe1ece3469192982cc42bca636fc01df", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:fe1ece3469192982cc42bca636fc01df:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.1f9c2e925fa135b510", "query_id": "gq_95345352ba55a57d7917", "job_id": "fe1ece3469192982cc42bca636fc01df", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/ec9950cb-ccb5-4d2b-b49d-0f6a80b03460", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/ec9950cb-ccb5-4d2b-b49d-0f6a80b03460", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2a1c293273db1f9147137cdf7abbecae", "title": "Senior AI Security Engineer", "employer_name": "Citigroup Inc.", "employer_slug": "citigroup", "location_text": "BUDAPEST, Hungary", "country": "HU", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://citi.eightfold.ai/careers/job/859034321080", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Security Engineer BUDAPEST, Hungary", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.e81a7e3f5615079b95", "query_id": "gq_95345352ba55a57d7917", "job_id": "2a1c293273db1f9147137cdf7abbecae", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2a1c293273db1f9147137cdf7abbecae:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034321080", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859034321080", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "07954639a6e38d2a55e2ece8fe0c5917", "title": "Senior Manager, Revenue Enablement", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-23T00:01:34.950Z", "apply_url": "https://jobs.ashbyhq.com/openai/0ad326fc-9e13-4390-9621-4735d02f8658", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Manager, Revenue Enablement San Francisco, California, United States About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Revenue team plays a critical role in enabling OpenAI to scale its commercial offerings - overseeing billing operations, deal desk, revenue systems, and revenue accounting. We work cross-functionally with Product, Engineering, and Go-To-Market teams to support new monetization strategies, improve operational efficiency, and maintain financial integrity as the business grows. About the Role As OpenAI scales monetization across self-serve, enterprise, partnerships, ads, and emerging business models, we need a strong operator to represent Revenue requirements throughout product and systems development. This role will sit at the center of Finance, Revenue Operations, and Business Platform teams to ensure revenue capabilities are designed, tested, and launched in a scalable and controlled way. This role will serve as the business-side owner for Revenue requirements, translating accounting, operational, billing, reporting, and controls needs into actionable requirements across Business Platform and Transformation teams. This person will drive process design, launch readiness, UAT, and continuous improvement across quote-to-cash and revenue operations workflows. This is an ideal role for someone who combines revenue domain expertise, operational judgment, structured problem solving, and strong cross-functional influence. You'll be responsible for: - Serve as Revenue's primary business representative for monetization, operational, and systems initiatives. - Define accounting, operational, billing, reporting, and controls requirements for new products and business models. - Translate Revenue Accounting, Billing Operations, Deal Desk, and Finance requirements into clear", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ab18e6ca1ee9811400", "query_id": "gq_95345352ba55a57d7917", "job_id": "07954639a6e38d2a55e2ece8fe0c5917", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Manager, Revenue Enablement San Francisco, California, United States About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Revenue team plays a critical role in enabling OpenAI to scale its commercial offerings - overseeing billing operations, deal desk, revenue systems, and revenue accounting. We work cross-functionally with Product, Engineering, and Go-To-Market teams to support new monetization strategies, improve operational efficiency, and maintain financial integrity as the business grows. About the Role As OpenAI scales monetization across self-serve, enterprise, partnerships, ads, and emerging business models, we need a strong operator to represent Revenue requirements throughout product and systems development. This role will sit at the center of Finance, Revenue Operations, and Business Platform teams to ensure revenue capabilities are designed, tested, and launched in a scalable and controlled way. This role will serve as the business-side owner for Revenue requirements, translating accounting, operational, billing, reporting, and controls needs into actionable requirements across Business Platform and Transformation teams. This person will drive process design, launch readiness, UAT, and continuous improvement across quote-to-cash and revenue operations workflows. This is an ideal role for someone who combines revenue domain expertise, operational judgment, structured problem solving, and strong cross-functional influence. You'll be responsible for: - Serve as Revenue's primary business representative for monetization, operational, and systems initiatives. - Define accounting, operational, billing, reporting, and controls requirements for new products and business models. - Translate Revenue Accounting, Billing Operations, Deal Desk, and Finance requirements into clear", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:07954639a6e38d2a55e2ece8fe0c5917:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.083c40c1c0c571c31d", "query_id": "gq_95345352ba55a57d7917", "job_id": "07954639a6e38d2a55e2ece8fe0c5917", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:07954639a6e38d2a55e2ece8fe0c5917:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e4988e88dc015e71b4", "query_id": "gq_95345352ba55a57d7917", "job_id": "07954639a6e38d2a55e2ece8fe0c5917", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0ad326fc-9e13-4390-9621-4735d02f8658", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0ad326fc-9e13-4390-9621-4735d02f8658", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "18e0bb8d4d165e00adcb2dc6b657bb4e", "title": "Technical Lead Manager, Data Engineering, Trust & Safety", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-04T03:48:06.794Z", "apply_url": "https://jobs.ashbyhq.com/openai/e1daa4e0-c42a-45a7-b9ee-559b35bfe08a", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Lead Manager, Data Engineering, Trust & Safety San Francisco, California, United States About the Team The Applied team brings OpenAI's technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will - Lead and grow a high-performing Trust & Safety Data Engineering team. - Define the roadmap", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 15, "years_experience_max": 15, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.693de2297c874f8e8a", "query_id": "gq_95345352ba55a57d7917", "job_id": "18e0bb8d4d165e00adcb2dc6b657bb4e", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Lead Manager, Data Engineering, Trust & Safety San Francisco, California, United States About the Team The Applied team brings OpenAI's technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will - Lead and grow a high-performing Trust & Safety Data Engineering team. - Define the roadmap", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:18e0bb8d4d165e00adcb2dc6b657bb4e:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.43304d59b1e0d93b45", "query_id": "gq_95345352ba55a57d7917", "job_id": "18e0bb8d4d165e00adcb2dc6b657bb4e", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:18e0bb8d4d165e00adcb2dc6b657bb4e:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.1d2001f7ec6dad707b", "query_id": "gq_95345352ba55a57d7917", "job_id": "18e0bb8d4d165e00adcb2dc6b657bb4e", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/e1daa4e0-c42a-45a7-b9ee-559b35bfe08a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/e1daa4e0-c42a-45a7-b9ee-559b35bfe08a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "85c0d262549b7cb423d0d8110d653eb1", "title": "Senior Machine Learning Engineer I", "employer_name": "RELX", "employer_slug": "relx", "location_text": "Shanghai", "country": "CN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-04T00:00:00.000Z", "apply_url": "https://relx.wd3.myworkdayjobs.com/relx/job/Shanghai/Senior-Machine-Learning-Engineer-II_R110527-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer I Shanghai posted: Posted 8 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.812bf5292ef4d24b4f", "query_id": "gq_95345352ba55a57d7917", "job_id": "85c0d262549b7cb423d0d8110d653eb1", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:85c0d262549b7cb423d0d8110d653eb1:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/Shanghai/Senior-Machine-Learning-Engineer-II_R110527-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/Shanghai/Senior-Machine-Learning-Engineer-II_R110527-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "231c09057f842d3ead8ac6dcd7c722ed", "title": "Data Science Manager, Integrity", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": true, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-02-03T14:10:01.963Z", "apply_url": "https://jobs.ashbyhq.com/openai/a10fac90-0639-4bfc-92b2-97b094f7edcb", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Science Manager, Integrity San Francisco, California, United States About the Team Integrity Data Science sits at the center of OpenAI's mission to deploy powerful AI responsibly. We help ensure people can trust our products by building measurement systems, experimentation practices, and detection/mitigation strategies that protect OpenAI and our users from misuse, fraud, and evolving adversarial behaviors. As the scope and urgency of Integrity work expands across product surfaces and go-to-market motion, we're hiring a dedicated Data Science Manager to scale the team, strengthen execution across multiple Integrity domains, and deepen partnership with Product, Engineering, Operations, and adjacent orgs (e.g., Growth, Ads). This role is based in our San Francisco HQ (in-office). About the Role As Data Science Manager, Integrity, you will lead a team of data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling. You'll be accountable for building a high-performing DS function that can keep pace with fast-moving threats-and for shaping the analytical strategy that informs how OpenAI detects, measures, and mitigates integrity risks at scale. This is a highly cross-functional leadership role. You'll help set the roadmap with Integrity Product/Engineering leaders, evolve team structure and operating rhythms, raise the bar on technical rigor (experimentation, causal inference, modeling, metrics), and develop a culture of proactive, high-leverage impact. Many of the challenges in this space are emergent-new misuse patterns appear as the technology and ecosystem evolves-so this role requires strong judgment, comfort with ambiguity, and an ability to build systems that scale. In this", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.8de86f256584016c2b", "query_id": "gq_95345352ba55a57d7917", "job_id": "231c09057f842d3ead8ac6dcd7c722ed", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Data Science Manager, Integrity San Francisco, California, United States About the Team Integrity Data Science sits at the center of OpenAI's mission to deploy powerful AI responsibly. We help ensure people can trust our products by building measurement systems, experimentation practices, and detection/mitigation strategies that protect OpenAI and our users from misuse, fraud, and evolving adversarial behaviors. As the scope and urgency of Integrity work expands across product surfaces and go-to-market motion, we're hiring a dedicated Data Science Manager to scale the team, strengthen execution across multiple Integrity domains, and deepen partnership with Product, Engineering, Operations, and adjacent orgs (e.g., Growth, Ads). This role is based in our San Francisco HQ (in-office). About the Role As Data Science Manager, Integrity, you will lead a team of data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling. You'll be accountable for building a high-performing DS function that can keep pace with fast-moving threats-and for shaping the analytical strategy that informs how OpenAI detects, measures, and mitigates integrity risks at scale. This is a highly cross-functional leadership role. You'll help set the roadmap with Integrity Product/Engineering leaders, evolve team structure and operating rhythms, raise the bar on technical rigor (experimentation, causal inference, modeling, metrics), and develop a culture of proactive, high-leverage impact. Many of the challenges in this space are emergent-new misuse patterns appear as the technology and ecosystem evolves-so this role requires strong judgment, comfort with ambiguity, and an ability to build systems that scale. In this", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:231c09057f842d3ead8ac6dcd7c722ed:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.09354637d6cc4e5244", "query_id": "gq_95345352ba55a57d7917", "job_id": "231c09057f842d3ead8ac6dcd7c722ed", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:231c09057f842d3ead8ac6dcd7c722ed:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.8b5e6ba77d76079dc4", "query_id": "gq_95345352ba55a57d7917", "job_id": "231c09057f842d3ead8ac6dcd7c722ed", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/a10fac90-0639-4bfc-92b2-97b094f7edcb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/a10fac90-0639-4bfc-92b2-97b094f7edcb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "b5d1ea58e0c163c4a7eba5449dfb39e0", "title": "AI application engineer", "employer_name": "STMicroelectronics", "employer_slug": "stmicroelectronics", "location_text": "Shenzhen, China", "country": "CN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://stmicroelectronics.eightfold.ai/careers/job/563637171789512", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI application engineer Shenzhen, China", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.205796682a4019b3c9", "query_id": "gq_95345352ba55a57d7917", "job_id": "b5d1ea58e0c163c4a7eba5449dfb39e0", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b5d1ea58e0c163c4a7eba5449dfb39e0:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637171789512", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637171789512", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "30804f7131cb27927bfa9fce7eeda365", "title": "AI Engineer", "employer_name": "Infosys Consulting", "employer_slug": "infosys-consulting", "location_text": "Location not specified", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=25633&siteid=5439&PageType=JobDetails&jobid=2246803", "apply_url_verified": false, "ats": "brassring_kenexa", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer Location - Bucharest,Timisoara,Cluj,Sibiu Business Unit - ADM Job Description Today, the corporate landscape is dynamic and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where ideas can flourish and where you are empowered to move forward as far as your ideas will take you. At Infosys, we assure that your career will never stand still, we will inspire you to build what's next and we will navigate further together. Our journey of learnability, values and trusted relationships with our clients continue to be the cornerstones of our organization and these values are upheld only because of our people. Your role - Autonomous task agents that plan, reason, and use tools to complete multi-step workflows -campaign QA, comms research, briefing preparation, document workflows. - Multi-agent systems where specialized agents collaborate under an orchestrator (e.g. researcher / writer / reviewer patterns). - Long-running agents with persistent memory, human-in-the-loop checkpoints, and approval gates suitable for enterprise use. Required - Strong programming skills in Python (typed, tested, production-ready). TypeScript / Node.js a plus. - Hands-on production experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI, or open-weight models). - Demonstrated experience designing agentic systems - fluency with at least one agent framework (LangGraph, AutoGen, CrewAI, Semantic Kernel) AND practical familiarity with multiple agent design patterns (ReAct, plan-and-execute, reflection, multi-agent). - Practical experience with retrieval systems and at least one vector database (pgvector, Pinecone, Weaviate, Azure", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Professional Services", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.662e4384067ff0c8a6", "query_id": "gq_95345352ba55a57d7917", "job_id": "30804f7131cb27927bfa9fce7eeda365", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "AI Engineer Location - Bucharest,Timisoara,Cluj,Sibiu Business Unit - ADM Job Description Today, the corporate landscape is dynamic and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where ideas can flourish and where you are empowered to move forward as far as your ideas will take you. At Infosys, we assure that your career will never stand still, we will inspire you to build what's next and we will navigate further together. Our journey of learnability, values and trusted relationships with our clients continue to be the cornerstones of our organization and these values are upheld only because of our people. Your role - Autonomous task agents that plan, reason, and use tools to complete multi-step workflows -campaign QA, comms research, briefing preparation, document workflows. - Multi-agent systems where specialized agents collaborate under an orchestrator (e.g. researcher / writer / reviewer patterns). - Long-running agents with persistent memory, human-in-the-loop checkpoints, and approval gates suitable for enterprise use. Required - Strong programming skills in Python (typed, tested, production-ready). TypeScript / Node.js a plus. - Hands-on production experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI, or open-weight models). - Demonstrated experience designing agentic systems - fluency with at least one agent framework (LangGraph, AutoGen, CrewAI, Semantic Kernel) AND practical familiarity with multiple agent design patterns (ReAct, plan-and-execute, reflection, multi-agent). - Practical experience with retrieval systems and at least one vector database (pgvector, Pinecone, Weaviate, Azure", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:30804f7131cb27927bfa9fce7eeda365:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.560d19d0b6151bbc63", "query_id": "gq_95345352ba55a57d7917", "job_id": "30804f7131cb27927bfa9fce7eeda365", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "AI Engineer Location - Bucharest,Timisoara,Cluj,Sibiu Business Unit - ADM Job Description Today, the corporate landscape is dynamic and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where ideas can flourish and where you are empowered to move forward as far as your ideas will take you. At Infosys, we assure that your career will never stand still, we will inspire you to build what's next and we will navigate further together. Our journey of learnability, values and trusted relationships with our clients continue to be the cornerstones of our organization and these values are upheld only because of our people. Your role - Autonomous task agents that plan, reason, and use tools to complete multi-step workflows -campaign QA, comms research, briefing preparation, document workflows. - Multi-agent systems where specialized agents collaborate under an orchestrator (e.g. researcher / writer / reviewer patterns). - Long-running agents with persistent memory, human-in-the-loop checkpoints, and approval gates suitable for enterprise use. Required - Strong programming skills in Python (typed, tested, production-ready). TypeScript / Node.js a plus. - Hands-on production experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI, or open-weight models). - Demonstrated experience designing agentic systems - fluency with at least one agent framework (LangGraph, AutoGen, CrewAI, Semantic Kernel) AND practical familiarity with multiple agent design patterns (ReAct, plan-and-execute, reflection, multi-agent). - Practical experience with retrieval systems and at least one vector database (pgvector, Pinecone, Weaviate, Azure", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=25633&siteid=5439&PageType=JobDetails&jobid=2246803", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=25633&siteid=5439&PageType=JobDetails&jobid=2246803", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "56bfcfa7b8c91578cfcc2a859740eeed", "title": "Senior AI – Computer Vision Engineer", "employer_name": "Occidental Petroleum", "employer_slug": "occidental-petroleum", "location_text": "Houston, Texas", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-20T00:00:00.000Z", "apply_url": "https://oxy.wd5.myworkdayjobs.com/Corporate/job/Houston-Texas/Senior-AI---Computer-Vision-Engineer_JR108173-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI – Computer Vision Engineer Houston, Texas posted: Posted 23 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/797468/000162828026009059/oxy-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/797468/000162828026009059/oxy-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.39478010cc2317e15c", "query_id": "gq_95345352ba55a57d7917", "job_id": "56bfcfa7b8c91578cfcc2a859740eeed", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:56bfcfa7b8c91578cfcc2a859740eeed:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/797468/000162828026009059/oxy-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/797468/000162828026009059/oxy-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://oxy.wd5.myworkdayjobs.com/Corporate/job/Houston-Texas/Senior-AI---Computer-Vision-Engineer_JR108173-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://oxy.wd5.myworkdayjobs.com/Corporate/job/Houston-Texas/Senior-AI---Computer-Vision-Engineer_JR108173-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "4f1295b35d1df9294582ed8c89cdecf5", "title": "Data Governance with AI/Gen AI", "employer_name": "Citigroup Inc.", "employer_slug": "citigroup", "location_text": "Chennai, Tamil Nādu, India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://citi.eightfold.ai/careers/job/859035574101", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Governance with AI/Gen AI Chennai, Tamil Nādu, India", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.445a0ecbdfc6aea14c", "query_id": "gq_95345352ba55a57d7917", "job_id": "4f1295b35d1df9294582ed8c89cdecf5", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4f1295b35d1df9294582ed8c89cdecf5:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859035574101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://citi.eightfold.ai/careers/job/859035574101", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "3f281a8e3defb3a7b29942654dd78b33", "title": "Enterprise 3P Field Events Lead", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 227000, "salary_max": 252000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 227000, "base_salary_max": 252000, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-23T03:31:18.386Z", "apply_url": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Enterprise 3P Field Events Lead San Francisco, California, United States About the Team The Enterprise Marketing team helps the world's largest organizations understand, adopt, and scale AI responsibly. We partner closely with Sales, Solutions, Product, Research, Customer Success, Events, Comms, and executive leadership to help customers see what is possible with OpenAI and move from interest to action. About the Role OpenAI needs a strategic field events leader who can make third-party events run at scale. As Enterprise Marketing expands across partner summits, priority industries, major conferences, and customer-facing field moments, the team needs someone who can turn a growing portfolio of external events into a disciplined, repeatable operating machine. The Enterprise 3P Field Events Lead will own the third-party field events motion for our enterprise segment. They will partner closely with Sales, Events, Product Marketing, Comms, Content, Design, and Marketing Operations to ensure OpenAI shows up in the right places, with the right goals, message, footprint, follow-through, and measurement. The right person has managed large third-party event portfolios at scale and understands how to connect sponsorships, field activations, partner moments, executive programs, sales goals, industry priorities, and post-event conversion into one operating system. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own the third-party field events portfolio, including partner summits, industry events, sponsored conferences, and high-priority external field activations. - Build annual and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 11, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d1b48a94c2fc66e153", "query_id": "gq_95345352ba55a57d7917", "job_id": "3f281a8e3defb3a7b29942654dd78b33", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Enterprise 3P Field Events Lead San Francisco, California, United States About the Team The Enterprise Marketing team helps the world's largest organizations understand, adopt, and scale AI responsibly. We partner closely with Sales, Solutions, Product, Research, Customer Success, Events, Comms, and executive leadership to help customers see what is possible with OpenAI and move from interest to action. About the Role OpenAI needs a strategic field events leader who can make third-party events run at scale. As Enterprise Marketing expands across partner summits, priority industries, major conferences, and customer-facing field moments, the team needs someone who can turn a growing portfolio of external events into a disciplined, repeatable operating machine. The Enterprise 3P Field Events Lead will own the third-party field events motion for our enterprise segment. They will partner closely with Sales, Events, Product Marketing, Comms, Content, Design, and Marketing Operations to ensure OpenAI shows up in the right places, with the right goals, message, footprint, follow-through, and measurement. The right person has managed large third-party event portfolios at scale and understands how to connect sponsorships, field activations, partner moments, executive programs, sales goals, industry priorities, and post-event conversion into one operating system. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own the third-party field events portfolio, including partner summits, industry events, sponsored conferences, and high-priority external field activations. - Build annual and", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:3f281a8e3defb3a7b29942654dd78b33:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.69a82e15b1c35a6afe", "query_id": "gq_95345352ba55a57d7917", "job_id": "3f281a8e3defb3a7b29942654dd78b33", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:3f281a8e3defb3a7b29942654dd78b33:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.7d87a5e67aa0ed890a", "query_id": "gq_95345352ba55a57d7917", "job_id": "3f281a8e3defb3a7b29942654dd78b33", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06a8c9e8-7ec8-455e-9193-ad46611c4d03", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4a2bd9d540a4bd84e4f154ee85575847", "title": "AIML - Sr Machine Learning Engineer - Answers, Knowledge & Information (AKI)", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Cupertino, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 181100, "salary_max": 318400, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 181100, "base_salary_max": 318400, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2025-08-08T22:31:58.614Z", "apply_url": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AIML - Sr Machine Learning Engineer - Answers, Knowledge & Information (AKI) Cupertino, United States of America The Answers, Knowledge and Information team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information! We are looking for a senior Machine Learning Engineer with a passion for building scalable, high quality solutions to evaluate personalized search applications. In this role, will directly impact how we assess and improve the quality of novel search applications by driving solutions for data generation, data quality assessment, offline and online metrics, and methods for statistical model and search quality assessment. Your work will impact the quality of innovative Search experiences across Apple products. In this role you will have the opportunity to develop data generation methodologies for personalized model and search systems evaluations, online and offline metrics for quality assessment and build scalable systems for comprehensive evaluation. Our team is responsible for models and evaluation of search experiences that answer user's questions using their personal documents with privacy at the forefront. Role responsibilities include: - Design and implement novel data generation and data", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 6, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.ac880718a8c54d0fac", "query_id": "gq_95345352ba55a57d7917", "job_id": "4a2bd9d540a4bd84e4f154ee85575847", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4a2bd9d540a4bd84e4f154ee85575847:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200615736/aiml-sr-machine-learning-engineer-answers-knowledge-information-aki?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "f5865cccf8f990ee0e4edcd2bd70c3b2", "title": "Edge AI Engineer", "employer_name": "Jabil", "employer_slug": "jabil", "location_text": "Penang", "country": "MY", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://jabil.wd5.myworkdayjobs.com/Jabil_Careers/job/Penang/Edge-AI-Engineer_J2444506", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Edge AI Engineer Penang posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/898293/000162828025045293/jbl-20250831.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/898293/000162828025045293/jbl-20250831.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.39efbb84e560838086", "query_id": "gq_95345352ba55a57d7917", "job_id": "f5865cccf8f990ee0e4edcd2bd70c3b2", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f5865cccf8f990ee0e4edcd2bd70c3b2:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/898293/000162828025045293/jbl-20250831.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/898293/000162828025045293/jbl-20250831.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jabil.wd5.myworkdayjobs.com/Jabil_Careers/job/Penang/Edge-AI-Engineer_J2444506", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jabil.wd5.myworkdayjobs.com/Jabil_Careers/job/Penang/Edge-AI-Engineer_J2444506", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "957da3183383480963b4f6ac12eb4a97", "title": "Engineering Manager, Core Services", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-02-02T02:41:09.849Z", "apply_url": "https://jobs.ashbyhq.com/openai/ebc65e7d-d86a-4066-aa82-3a7758d97bb6", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Engineering Manager, Core Services San Francisco, California, United States About the Team The Core Services organization builds and runs the mission-critical online services that product teams rely on in production. We own foundational distributed systems and platform capabilities that enable reliable execution, high-performance services, and large-scale file/data needs across our products. This team is distinct from developer infrastructure and data infrastructure-our focus is production service foundations and core runtime services. About the Role We're hiring an Engineering Manager, Core Services to help lead teams responsible for highly reliable, high-scale distributed systems that sit on the critical path for OpenAI products. Your team will own foundational production systems that OpenAI's product engineering teams build on. You'll collaborate closely with product and infrastructure partners to ship reliable services quickly, and help scale systems and teams as OpenAI grows. You'll partner closely with senior engineering leaders to scale the org, mature operations, and drive major platform initiatives. This role requires strong technical ability. You'll be responsible for: - Managing and growing a high-performing, team of infrastructure engineers. - Leading teams building and operating large, critical production platforms, including cluster reliability, scaling, and rollout safety. - Building and operating mission-critical distributed systems with strong operational rigor (SLOs, incident response, capacity planning, reliability). - Setting technical direction for platform foundations such as workflow/orchestration capabilities, large-scale file/blob/storage services, and core service foundations. - Partnering with a broad set of stakeholders, including product engineering, adjacent infrastructure teams, and (where relevant) finance/cost partners. - Coaching, mentoring, and developing", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.922bb0d29df6b6b487", "query_id": "gq_95345352ba55a57d7917", "job_id": "957da3183383480963b4f6ac12eb4a97", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Engineering Manager, Core Services San Francisco, California, United States About the Team The Core Services organization builds and runs the mission-critical online services that product teams rely on in production. We own foundational distributed systems and platform capabilities that enable reliable execution, high-performance services, and large-scale file/data needs across our products. This team is distinct from developer infrastructure and data infrastructure-our focus is production service foundations and core runtime services. About the Role We're hiring an Engineering Manager, Core Services to help lead teams responsible for highly reliable, high-scale distributed systems that sit on the critical path for OpenAI products. Your team will own foundational production systems that OpenAI's product engineering teams build on. You'll collaborate closely with product and infrastructure partners to ship reliable services quickly, and help scale systems and teams as OpenAI grows. You'll partner closely with senior engineering leaders to scale the org, mature operations, and drive major platform initiatives. This role requires strong technical ability. You'll be responsible for: - Managing and growing a high-performing, team of infrastructure engineers. - Leading teams building and operating large, critical production platforms, including cluster reliability, scaling, and rollout safety. - Building and operating mission-critical distributed systems with strong operational rigor (SLOs, incident response, capacity planning, reliability). - Setting technical direction for platform foundations such as workflow/orchestration capabilities, large-scale file/blob/storage services, and core service foundations. - Partnering with a broad set of stakeholders, including product engineering, adjacent infrastructure teams, and (where relevant) finance/cost partners. - Coaching, mentoring, and developing", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:957da3183383480963b4f6ac12eb4a97:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.59748b5ff120dc3310", "query_id": "gq_95345352ba55a57d7917", "job_id": "957da3183383480963b4f6ac12eb4a97", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:957da3183383480963b4f6ac12eb4a97:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f4060c2dfb0fee8227", "query_id": "gq_95345352ba55a57d7917", "job_id": "957da3183383480963b4f6ac12eb4a97", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/ebc65e7d-d86a-4066-aa82-3a7758d97bb6", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/ebc65e7d-d86a-4066-aa82-3a7758d97bb6", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "188c196e449ded279f543b784f07464a", "title": "Senior Machine Learning Engineer, Proactive - Apple Intelligence Data Platform", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Seattle, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 139500, "salary_max": 258100, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 139500, "base_salary_max": 258100, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-11T23:51:15.097Z", "apply_url": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer, Proactive - Apple Intelligence Data Platform Seattle, United States of America Are you excited about building innovative generative AI experiences that empower millions of users daily? Do you thrive in collaborative environments and enjoy applying your machine learning expertise to real-world user experiences? If so, we'd love to hear from you. We're looking for a Senior Machine Learning Engineer to join the Apple Intelligence Data Platform team. This team powers key intelligence features across Apple's ecosystem - including Siri Suggestions, the Shortcuts app, and more - by building scalable, privacy-conscious ML systems! Our team is responsible for the Research, Development and Deployment of the core platform that powers Apple Intelligence on device and on private compute cloud - adapters, speculative decoding, guided generation to name a few. Our team is responsible for underpinning all the Apple Intelligence features we shipped to our customers including Writing Tools, Notification Summaries, ChatGPT integration, Siri and more. Our team has a great mix of talent across Machine Learning and Software Engineering. We love to share our knowledge within our team, stay abreast of state-of-the-art and deliver outstanding products for our users. We also have a strong culture of multi-functional collaboration across teams at Apple. Proactive Intelligence is central to Apple Intelligence. We're building a contextual, on-device platform that anticipates user needs - from predicting which app you'll launch next to understanding the difference between work and leisure modes. This is your opportunity to help shape the next generation of personal,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.f90ba9c475aa53c366", "query_id": "gq_95345352ba55a57d7917", "job_id": "188c196e449ded279f543b784f07464a", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:188c196e449ded279f543b784f07464a:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200625093/senior-machine-learning-engineer-proactive-apple-intelligence-data-platform?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "9ed5b654b737ac0839463c0d08b50878", "title": "Software Engineer, Habitat (Online Data)", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Seattle, Washington, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2025-04-14T21:41:35.324Z", "apply_url": "https://jobs.ashbyhq.com/openai/460b4295-3803-4dda-983d-3b0fea0b0fc4", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Habitat (Online Data) Seattle, Washington, United States About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI's online user data. As OpenAI's scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: - Provisioning and developer experience - APIs and guardrails - Scaling, performance, and reliability - Data movement, caching, routing, and placement - Privacy enforcement and access control - Change Data Capture (CDC) as a first-class primitive - The foundation for future storage backends You'll work on the core online database platform behind OpenAI's products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You'll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will - Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement - Own a major surface area end to end, from product and API design to operational excellence - Improve latency, correctness, and cost efficiency for real production workloads at massive scale - Build strong instrumentation, debugging workflows, and developer-first tooling - Collaborate closely with internal product and infrastructure teams to understand", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.6ce26cf81038974b0f", "query_id": "gq_95345352ba55a57d7917", "job_id": "9ed5b654b737ac0839463c0d08b50878", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Habitat (Online Data) Seattle, Washington, United States About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI's online user data. As OpenAI's scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: - Provisioning and developer experience - APIs and guardrails - Scaling, performance, and reliability - Data movement, caching, routing, and placement - Privacy enforcement and access control - Change Data Capture (CDC) as a first-class primitive - The foundation for future storage backends You'll work on the core online database platform behind OpenAI's products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You'll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will - Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement - Own a major surface area end to end, from product and API design to operational excellence - Improve latency, correctness, and cost efficiency for real production workloads at massive scale - Build strong instrumentation, debugging workflows, and developer-first tooling - Collaborate closely with internal product and infrastructure teams to understand", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9ed5b654b737ac0839463c0d08b50878:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.686cc723e67807271b", "query_id": "gq_95345352ba55a57d7917", "job_id": "9ed5b654b737ac0839463c0d08b50878", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9ed5b654b737ac0839463c0d08b50878:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.72f136c8e35c8a149f", "query_id": "gq_95345352ba55a57d7917", "job_id": "9ed5b654b737ac0839463c0d08b50878", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/460b4295-3803-4dda-983d-3b0fea0b0fc4", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/460b4295-3803-4dda-983d-3b0fea0b0fc4", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "aa9b1dec57aee5edd2456525cc78907a", "title": "Data Center Infrastructure Engineering Program Manager (Network and Whitespace)", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-20T21:46:38.359Z", "apply_url": "https://jobs.ashbyhq.com/openai/0ed12b35-0115-4ad3-81f5-ea1bb05c9f6b", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Center Infrastructure Engineering Program Manager (Network and Whitespace) San Francisco, California, United States About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Engineering Program Manager, you will help turn complex infrastructure strategy into executable programs across electrical, mechanical, controls, network, hardware, construction, commissioning, deployment, and operations workstreams. You will partner with research, hardware engineering, data center engineering, site development, supply chain, security, EHS, finance, legal, operations, and external delivery partners to bring OpenAI's infrastructure vision to life. About the Role We are looking for an Engineering Program Manager (EPM) to lead assigned infrastructure programs focused on production and non-production network integration, controls coordination, and the design and deployment of data hall or whitespace facilities. The EPM will support functional Directly Responsible Individuals (DRIs) across network, controls, structural, electrical, and mechanical disciplines. Key responsibilities include coordinating assigned workstreams and program controls, maintaining risks and interfaces, and supporting readiness within the network and data hall deployment track. The ideal candidate thrives on bringing structure to complex environments characterized by ambiguous technical requirements, large partner ecosystems, tight deadlines, and high operational stakes. This individual must be adept at keeping teams aligned on decisions, risks, dependencies, schedules, and readiness criteria, and escalating gaps or decision points when needed. Candidates should have a proven track", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.c4352d52fc3c4b1d32", "query_id": "gq_95345352ba55a57d7917", "job_id": "aa9b1dec57aee5edd2456525cc78907a", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Data Center Infrastructure Engineering Program Manager (Network and Whitespace) San Francisco, California, United States About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Engineering Program Manager, you will help turn complex infrastructure strategy into executable programs across electrical, mechanical, controls, network, hardware, construction, commissioning, deployment, and operations workstreams. You will partner with research, hardware engineering, data center engineering, site development, supply chain, security, EHS, finance, legal, operations, and external delivery partners to bring OpenAI's infrastructure vision to life. About the Role We are looking for an Engineering Program Manager (EPM) to lead assigned infrastructure programs focused on production and non-production network integration, controls coordination, and the design and deployment of data hall or whitespace facilities. The EPM will support functional Directly Responsible Individuals (DRIs) across network, controls, structural, electrical, and mechanical disciplines. Key responsibilities include coordinating assigned workstreams and program controls, maintaining risks and interfaces, and supporting readiness within the network and data hall deployment track. The ideal candidate thrives on bringing structure to complex environments characterized by ambiguous technical requirements, large partner ecosystems, tight deadlines, and high operational stakes. This individual must be adept at keeping teams aligned on decisions, risks, dependencies, schedules, and readiness criteria, and escalating gaps or decision points when needed. Candidates should have a proven track", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:aa9b1dec57aee5edd2456525cc78907a:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a1e3f8785c858aba6c", "query_id": "gq_95345352ba55a57d7917", "job_id": "aa9b1dec57aee5edd2456525cc78907a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:aa9b1dec57aee5edd2456525cc78907a:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a5ccb9bc604356969b", "query_id": "gq_95345352ba55a57d7917", "job_id": "aa9b1dec57aee5edd2456525cc78907a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0ed12b35-0115-4ad3-81f5-ea1bb05c9f6b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/0ed12b35-0115-4ad3-81f5-ea1bb05c9f6b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "78315604d123257de6a462223d8f5766", "title": "Machine Learning Engineer", "employer_name": "Arena", "employer_slug": "arena", "location_text": "Bay Area, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z" ], "posted_at": "2025-12-18T08:42:21.907Z", "apply_url": "https://jobs.ashbyhq.com/arena/eaeb1f28-cca9-468d-abcf-5ff412ad75de", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer Bay Area, California, United States About Arena Intelligence Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it. Tens of millions of people use Arena each month to evaluate how frontier systems handle the work they actually do. The preferences they share power the most transparent, rigorous, and human-centered evaluations in AI. Leading AI labs, enterprises, and independent researchers rely on our work and open datasets to understand how models behave in real workflows: agentic coding, creative generation, professional productivity, and beyond. We go beyond leaderboards and decompose what human experience reveals about AI, so models advance toward the work people actually do. We're a team of researchers, academics, builders, and creatives from UC Berkeley, Google, Stanford, and DeepMind. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We're building a company where thoughtful, curious people from all backgrounds can do their best work together, in an office culture that radiates excellence, energy, and focus. About the Role Arena Intelligence is seeking a Senior Machine Learning Engineer to help scale and strengthen the core infrastructure that powers real-world AI evaluation. You'll play a foundational role in shaping how we build, deploy, and improve our model benchmarking systems, working across data pipelines, inference APIs,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 4, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Media", "employer_industry_source": "source_sector", "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.eaf63751ccc2f291be", "query_id": "gq_95345352ba55a57d7917", "job_id": "78315604d123257de6a462223d8f5766", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:78315604d123257de6a462223d8f5766:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/arena/eaeb1f28-cca9-468d-abcf-5ff412ad75de", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/arena/eaeb1f28-cca9-468d-abcf-5ff412ad75de", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/arena/eaeb1f28-cca9-468d-abcf-5ff412ad75de", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/arena/eaeb1f28-cca9-468d-abcf-5ff412ad75de", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "a6d9cba0714096d91583d3b88c74cbad", "title": "Senior Machine Learning Engineer", "employer_name": "Equifax", "employer_slug": "equifax", "location_text": "IRL - County Wexford - Wexford", "country": "IE", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T00:00:00.000Z", "apply_url": "https://equifax.wd5.myworkdayjobs.com/External/job/IRL---County-Wexford---Wexford/Senior-Machine-Learning-Engineer_J00176887-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer IRL - County Wexford - Wexford posted: Posted 2 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/33185/000003318526000010/efx-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/33185/000003318526000010/efx-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Finance", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.adae5378a2e067c518", "query_id": "gq_95345352ba55a57d7917", "job_id": "a6d9cba0714096d91583d3b88c74cbad", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:a6d9cba0714096d91583d3b88c74cbad:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/33185/000003318526000010/efx-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/33185/000003318526000010/efx-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://equifax.wd5.myworkdayjobs.com/External/job/IRL---County-Wexford---Wexford/Senior-Machine-Learning-Engineer_J00176887-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://equifax.wd5.myworkdayjobs.com/External/job/IRL---County-Wexford---Wexford/Senior-Machine-Learning-Engineer_J00176887-1", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "b005dfb165c163b612c939f9ed5e2860", "title": "Software Engineer, Build Systems / CI", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, Seattle, New York City", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-25T19:44:52.128Z", "apply_url": "https://jobs.ashbyhq.com/openai/202eb061-23d7-4a58-80c8-bc3b41e56d39", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Build Systems / CI San Francisco, California, United States, Seattle, New York City About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will - Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. - Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. - Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. - Build systems that reduce unnecessary CI work through affected-target detection,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.fa4c84a32ba1753142", "query_id": "gq_95345352ba55a57d7917", "job_id": "b005dfb165c163b612c939f9ed5e2860", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Build Systems / CI San Francisco, California, United States, Seattle, New York City About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will - Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. - Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. - Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. - Build systems that reduce unnecessary CI work through affected-target detection,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b005dfb165c163b612c939f9ed5e2860:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.47bffbf97f282f50a4", "query_id": "gq_95345352ba55a57d7917", "job_id": "b005dfb165c163b612c939f9ed5e2860", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:b005dfb165c163b612c939f9ed5e2860:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.8eceb70fdfe86d1e61", "query_id": "gq_95345352ba55a57d7917", "job_id": "b005dfb165c163b612c939f9ed5e2860", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/202eb061-23d7-4a58-80c8-bc3b41e56d39", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/202eb061-23d7-4a58-80c8-bc3b41e56d39", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "bc47ed3da8fa450a9e8ef22d4e96a14a", "title": "Deal Desk Lead, Cloud Marketplaces & Partnerships — AWS Focus", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-28T21:24:04.174Z", "apply_url": "https://jobs.ashbyhq.com/openai/30d32d0b-26ba-4ce4-a164-d8d00a3ef1a1", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Deal Desk Lead, Cloud Marketplaces & Partnerships — AWS Focus San Francisco, California, United States About the Team OpenAI's Finance and Revenue Operations organization builds the commercial infrastructure that enables the business to scale with speed, discipline, and financial integrity. Deal Desk partners closely with Sales, Partnerships, Legal, Technical Revenue, Finance, Order Management, Billing Operations, Product, and GTM Systems to structure and execute complex enterprise transactions. We help the business move quickly while ensuring commercial agreements are executable, scalable, and supported by strong operational and financial controls. As OpenAI expands its strategic cloud partnership motions (AWS), Deal Desk will play an important role in establishing the commercial workflows, guardrails, and execution mechanisms needed to support partner-led and marketplace-enabled enterprise transactions. About the Role We are hiring a Deal Desk Lead, Cloud Marketplaces & Partnerships - AWS Focus to lead the commercial execution framework for cloud-partner transactions. This role will focus on supporting the AWS and OpenAI partnership, including AWS Marketplace and other partner-led enterprise commercial motions. This is an individual contributor role for someone who combines strong enterprise deal judgment with operational rigor and a builder mindset. You will Translate complex AWS partner-led transactions into executable commercial structures, approvals, and repeatable Deal Desk processes. You will not own partner relationship management, pipeline generation, or sales closing. Instead, you will own the Deal Desk execution and governance layer that helps AWS-related opportunities move efficiently without creating unmanaged downstream risk across contracting, billing, revenue recognition, provisioning, reporting, controls, auditability, or customer experience.", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.7489d3f5164b4c2804", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc47ed3da8fa450a9e8ef22d4e96a14a", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Deal Desk Lead, Cloud Marketplaces & Partnerships — AWS Focus San Francisco, California, United States About the Team OpenAI's Finance and Revenue Operations organization builds the commercial infrastructure that enables the business to scale with speed, discipline, and financial integrity. Deal Desk partners closely with Sales, Partnerships, Legal, Technical Revenue, Finance, Order Management, Billing Operations, Product, and GTM Systems to structure and execute complex enterprise transactions. We help the business move quickly while ensuring commercial agreements are executable, scalable, and supported by strong operational and financial controls. As OpenAI expands its strategic cloud partnership motions (AWS), Deal Desk will play an important role in establishing the commercial workflows, guardrails, and execution mechanisms needed to support partner-led and marketplace-enabled enterprise transactions. About the Role We are hiring a Deal Desk Lead, Cloud Marketplaces & Partnerships - AWS Focus to lead the commercial execution framework for cloud-partner transactions. This role will focus on supporting the AWS and OpenAI partnership, including AWS Marketplace and other partner-led enterprise commercial motions. This is an individual contributor role for someone who combines strong enterprise deal judgment with operational rigor and a builder mindset. You will Translate complex AWS partner-led transactions into executable commercial structures, approvals, and repeatable Deal Desk processes. You will not own partner relationship management, pipeline generation, or sales closing. Instead, you will own the Deal Desk execution and governance layer that helps AWS-related opportunities move efficiently without creating unmanaged downstream risk across contracting, billing, revenue recognition, provisioning, reporting, controls, auditability, or customer experience.", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:bc47ed3da8fa450a9e8ef22d4e96a14a:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.b4dc994d6f9c2df6d2", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc47ed3da8fa450a9e8ef22d4e96a14a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:bc47ed3da8fa450a9e8ef22d4e96a14a:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.7d9a6b737fcf6ebe7e", "query_id": "gq_95345352ba55a57d7917", "job_id": "bc47ed3da8fa450a9e8ef22d4e96a14a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/30d32d0b-26ba-4ce4-a164-d8d00a3ef1a1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/30d32d0b-26ba-4ce4-a164-d8d00a3ef1a1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "0a5272e841127b6f88debe0640507e88", "title": "AI Tutor - Dutch", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Remote", "country": "unknown", "employment_type": "part_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 35, "salary_max": 45, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 35, "base_salary_max": 45, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2026-03-27T09:05:14.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Dutch Remote ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor specialized in multilingual audio capabilities, you will contribute to xAI's mission by training and refining Grok to excel in voice interactions, speech recognition, and auditory experiences across diverse languages, accents, and cultural contexts. Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances. RESPONSIBILITIES: - Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages. - Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "portfolio_required": { "field": "portfolio_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "portfolio_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.b626d331d1355540e8", "query_id": "gq_95345352ba55a57d7917", "job_id": "0a5272e841127b6f88debe0640507e88", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "teaching_education", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0a5272e841127b6f88debe0640507e88:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090197007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "10010c1655808cbafcbbc203600a3fba", "title": "AI Tutor - Finnish", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Remote", "country": "unknown", "employment_type": "part_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 35, "salary_max": 45, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 35, "base_salary_max": 45, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2026-04-01T04:38:02.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Finnish Remote ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor specialized in multilingual audio capabilities, you will contribute to xAI's mission by training and refining Grok to excel in voice interactions, speech recognition, and auditory experiences across diverse languages, accents, and cultural contexts. Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances. RESPONSIBILITIES: - Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages. - Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "portfolio_required": { "field": "portfolio_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "portfolio_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.9b2b7b2ca569d36a04", "query_id": "gq_95345352ba55a57d7917", "job_id": "10010c1655808cbafcbbc203600a3fba", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "teaching_education", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:10010c1655808cbafcbbc203600a3fba:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/5090199007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "d08737666c166b15bd285e8bac8b5efe", "title": "Compensation Operations Lead", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-28T16:11:37.404Z", "apply_url": "https://jobs.ashbyhq.com/openai/d336dea8-d064-4964-8534-20526b4dbc2a", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Compensation Operations Lead San Francisco, California, United States About the Team OpenAI's mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. This long-term undertaking brings together the world's leading scientists, engineers, and business professionals to develop and deploy transformative AI technologies. Our Go-To-Market (GTM) organization helps customers understand, adopt, and scale OpenAI's products and platform. Revenue Operations partners closely with Sales, Finance, and People teams to drive planning, performance management, and operational excellence across the business. The Planning team leads key revenue planning cycles and helps align resources, incentives, and execution against company priorities. About the Role We are seeking a Compensation Operations Lead to build and scale the operational infrastructure supporting OpenAI's global variable compensation programs across Sales, Technical Success, Partnerships, and other GTM teams. This role owns the systems, processes, administration, and execution of compensation operations-including plan administration, compensation tooling, payout cycles, governance, and field support. Partnering closely with Revenue Operations, Finance, Total Rewards, HRIS, and GTM Systems, you will ensure compensation programs are accurate, scalable, compliant, and trusted by the field. The ideal candidate combines deep compensation operations expertise with strong systems thinking, operational rigor, and a customer-service mindset. You'll be responsible for: Compensation Operations - Administer compensation plans, quotas, credits, adjustments, exceptions, and payout processes. - Manage compensation workflows, approvals, and annual planning cycles. - Support compensation launches, plan changes, and operational readiness across GTM teams. - Design scalable processes that ensure accurate and efficient compensation administration. Systems & Tooling -", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "hr", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.f3bfe2c0f0e5ef68c6", "query_id": "gq_95345352ba55a57d7917", "job_id": "d08737666c166b15bd285e8bac8b5efe", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Compensation Operations Lead San Francisco, California, United States About the Team OpenAI's mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. This long-term undertaking brings together the world's leading scientists, engineers, and business professionals to develop and deploy transformative AI technologies. Our Go-To-Market (GTM) organization helps customers understand, adopt, and scale OpenAI's products and platform. Revenue Operations partners closely with Sales, Finance, and People teams to drive planning, performance management, and operational excellence across the business. The Planning team leads key revenue planning cycles and helps align resources, incentives, and execution against company priorities. About the Role We are seeking a Compensation Operations Lead to build and scale the operational infrastructure supporting OpenAI's global variable compensation programs across Sales, Technical Success, Partnerships, and other GTM teams. This role owns the systems, processes, administration, and execution of compensation operations-including plan administration, compensation tooling, payout cycles, governance, and field support. Partnering closely with Revenue Operations, Finance, Total Rewards, HRIS, and GTM Systems, you will ensure compensation programs are accurate, scalable, compliant, and trusted by the field. The ideal candidate combines deep compensation operations expertise with strong systems thinking, operational rigor, and a customer-service mindset. You'll be responsible for: Compensation Operations - Administer compensation plans, quotas, credits, adjustments, exceptions, and payout processes. - Manage compensation workflows, approvals, and annual planning cycles. - Support compensation launches, plan changes, and operational readiness across GTM teams. - Design scalable processes that ensure accurate and efficient compensation administration. Systems & Tooling -", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d08737666c166b15bd285e8bac8b5efe:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.7d6010fbcedfec64ce", "query_id": "gq_95345352ba55a57d7917", "job_id": "d08737666c166b15bd285e8bac8b5efe", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:d08737666c166b15bd285e8bac8b5efe:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.79ff44ffc940e94fcb", "query_id": "gq_95345352ba55a57d7917", "job_id": "d08737666c166b15bd285e8bac8b5efe", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d336dea8-d064-4964-8534-20526b4dbc2a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d336dea8-d064-4964-8534-20526b4dbc2a", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "e00cfdf065c48759cc1f2c03f7194d33", "title": "Member of Technical Staff - Recommendation Systems", "employer_name": "xAI", "employer_slug": "xai", "location_text": "Palo Alto, CA", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 180000, "salary_max": 440000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 180000, "base_salary_max": 440000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z", "sequoia" ], "posted_at": "2025-04-11T03:21:31.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Member of Technical Staff - Recommendation Systems Palo Alto, CA ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We're seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You'll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences. RESPONSIBILITIES: - Designing and architecting recommendation algorithms across various product surfaces - Leverage all of xAI's infra and AI stacks to dramatically enhance the user experience - Write data pipelines and training jobs that continuously learn from product data. - Iterate and improve the algorithm by gathering user feedback in real time through experimentation - Ensuring scalability", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.bf4137bddbad8aec15", "query_id": "gq_95345352ba55a57d7917", "job_id": "e00cfdf065c48759cc1f2c03f7194d33", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:e00cfdf065c48759cc1f2c03f7194d33:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/xai/jobs/4703144007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "e351198ff317f65fc81cd48511624d34", "title": "AI Deployment Engineering Manager, Startups", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, New York City", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-19T20:05:22.881Z", "apply_url": "https://jobs.ashbyhq.com/openai/7bdb15f0-1e3b-4352-b948-47fb35f25d71", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Deployment Engineering Manager, Startups San Francisco, California, United States, New York City About the Team The AI Deployment Engineering team partners closely with customers to help them move from experimentation to production with OpenAI's technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an AI Deployment Engineering Manager, Startups to lead and scale the Startups AI Deployment Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI. This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams. In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In This Role, You Will - Craft and continuously refine the strategic vision and operating model for the Startups AI Deployment Engineering team, aligning", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.4965aa471d0a4ae666", "query_id": "gq_95345352ba55a57d7917", "job_id": "e351198ff317f65fc81cd48511624d34", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "AI Deployment Engineering Manager, Startups San Francisco, California, United States, New York City About the Team The AI Deployment Engineering team partners closely with customers to help them move from experimentation to production with OpenAI's technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an AI Deployment Engineering Manager, Startups to lead and scale the Startups AI Deployment Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI. This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams. In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In This Role, You Will - Craft and continuously refine the strategic vision and operating model for the Startups AI Deployment Engineering team, aligning", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:e351198ff317f65fc81cd48511624d34:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.af21a1aeffaefef4a6", "query_id": "gq_95345352ba55a57d7917", "job_id": "e351198ff317f65fc81cd48511624d34", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:e351198ff317f65fc81cd48511624d34:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.9cf8671ad49b606526", "query_id": "gq_95345352ba55a57d7917", "job_id": "e351198ff317f65fc81cd48511624d34", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/7bdb15f0-1e3b-4352-b948-47fb35f25d71", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/7bdb15f0-1e3b-4352-b948-47fb35f25d71", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "61463a707ebf5cca6d4c21111cb34630", "title": "Principal AI Agent Engineer", "employer_name": "Zoom Communications, Inc.", "employer_slug": "zoom-communications", "location_text": "Seattle (WA)", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Senior-Machine-Learning-Engineer_R17895-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Principal AI Agent Engineer Seattle (WA) posted:", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.05c76ae27f09a51ecd", "query_id": "gq_95345352ba55a57d7917", "job_id": "61463a707ebf5cca6d4c21111cb34630", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:61463a707ebf5cca6d4c21111cb34630:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1585521/000158552126000030/zm-20260131.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Senior-Machine-Learning-Engineer_R17895-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zoom.wd5.myworkdayjobs.com/zoom/job/Seattle-WA/Senior-Machine-Learning-Engineer_R17895-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "56acd2f33bfe80093e10f24c869d012d", "title": "AI Engineering Manager | Remote | Europe", "employer_name": "n8n", "employer_slug": "n8n", "location_text": "Berlin Office, Berlin, Berlin-Brandenburg, Germany, Albania, Bulgaria, Bosnia, Croatia, Czech Republic, Estonia, Hungary, Kosovo, Latvia, Lithuania, Moldova, Montenegro, Poland, Romania, Serbia, Slovakia, Slovenia, Denmark, Finland, Norway, Sweden, Greece, Italy, Portugal, Spain, London Office, United Kingdom, Austria, Belgium, France, Ireland, Netherlands", "country": "unknown", "employment_type": "contract", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "EUR", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": 4, "match_401k_pct_source": "llm:greenfield:inv_371_postfix", "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn", "sequoia" ], "posted_at": "2026-04-13T09:32:19.081Z", "apply_url": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineering Manager | Remote | Europe Berlin Office, Berlin, Berlin-Brandenburg, Germany, Albania, Bulgaria, Bosnia, Croatia, Czech Republic, Estonia, Hungary, Kosovo, Latvia, Lithuania, Moldova, Montenegro, Poland, Romania, Serbia, Slovakia, Slovenia, Denmark, Finland, Norway, Sweden, Greece, Italy, Portugal, Spain, London Office, United Kingdom, Austria, Belgium, France, Ireland, Netherlands The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we're changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we've grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we've: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world's Top 40 most popular projects - Backed by top investors, from Sequoia's first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That's the company we've built. Now we'd love to see what you can build. If you're applying, try n8n out - whether you're technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register . We're", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": 30, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "pto_days": { "field": "pto_days", "source": "llm:greenfield:inv_371_postfix", "db_column": "pto_days" }, "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "match_401k_pct": { "field": "match_401k_pct", "source": "llm:greenfield:inv_371_postfix", "db_column": "match_401k_pct" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.de5db293329681fefc", "query_id": "gq_95345352ba55a57d7917", "job_id": "56acd2f33bfe80093e10f24c869d012d", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:56acd2f33bfe80093e10f24c869d012d:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "pto_days": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "match_401k_pct": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/n8n/f814f5ce-b615-413d-bbe0-b5786b3872e9", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "f1d144e6b46b430fb0f1739783675a50", "title": "Senior Manager, People Compliance", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-03-17T00:34:05.344Z", "apply_url": "https://jobs.ashbyhq.com/openai/97f5cbd7-979e-4343-bc77-5b39aedacb9a", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Manager, People Compliance San Francisco, California, United States About the Team OpenAI's People Team hires, engages, and supports world-class talent from diverse backgrounds to help build and deploy beneficial AGI. The People Compliance and Standards team brings together deep expertise in people policy, compliance, and workplace practices. We play a critical role in shaping how OpenAI supports its people through complexity, rapid growth, and change, ensuring our policies are thoughtful, scalable, and aligned with our values. About the Role We're seeking a Senior Manager, People Compliance to design, execute, and improve global People Compliance programs. Reporting to the Head of People Standards & Compliance, this role leads cross-functional initiatives, assesses regulatory impacts, and operationalizes compliant, scalable people processes aligned with OpenAI's goals. You'll partner closely with Legal, People, Finance, L&D, and other teams to ensure programs are effective, auditable, and scalable. Responsibilities - Lead global People Compliance initiatives across timelines, stakeholders, and execution - Assess employment laws (e.g., FLSA, ADA, FMLA, GDPR) and support policy updates - Draft and maintain policies, standards, and internal guidance - Support audits, risk assessments, and mitigation efforts - Build and maintain compliant, accessible documentation frameworks - Partner cross-functionally on compliance across records, immigration, classification, and expansion - Track metrics, build dashboards, and provide data-driven insights - Support compliance training development, rollout, and tracking - Assist with audits, regulatory reviews, and government filings - Stay current on global employment laws and support risk planning - Contribute to global compliance goals and organizational growth We're", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "finance", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.c97c11a77c17bf1d48", "query_id": "gq_95345352ba55a57d7917", "job_id": "f1d144e6b46b430fb0f1739783675a50", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Manager, People Compliance San Francisco, California, United States About the Team OpenAI's People Team hires, engages, and supports world-class talent from diverse backgrounds to help build and deploy beneficial AGI. The People Compliance and Standards team brings together deep expertise in people policy, compliance, and workplace practices. We play a critical role in shaping how OpenAI supports its people through complexity, rapid growth, and change, ensuring our policies are thoughtful, scalable, and aligned with our values. About the Role We're seeking a Senior Manager, People Compliance to design, execute, and improve global People Compliance programs. Reporting to the Head of People Standards & Compliance, this role leads cross-functional initiatives, assesses regulatory impacts, and operationalizes compliant, scalable people processes aligned with OpenAI's goals. You'll partner closely with Legal, People, Finance, L&D, and other teams to ensure programs are effective, auditable, and scalable. Responsibilities - Lead global People Compliance initiatives across timelines, stakeholders, and execution - Assess employment laws (e.g., FLSA, ADA, FMLA, GDPR) and support policy updates - Draft and maintain policies, standards, and internal guidance - Support audits, risk assessments, and mitigation efforts - Build and maintain compliant, accessible documentation frameworks - Partner cross-functionally on compliance across records, immigration, classification, and expansion - Track metrics, build dashboards, and provide data-driven insights - Support compliance training development, rollout, and tracking - Assist with audits, regulatory reviews, and government filings - Stay current on global employment laws and support risk planning - Contribute to global compliance goals and organizational growth We're", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f1d144e6b46b430fb0f1739783675a50:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.1ba0ced182a99f6db3", "query_id": "gq_95345352ba55a57d7917", "job_id": "f1d144e6b46b430fb0f1739783675a50", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f1d144e6b46b430fb0f1739783675a50:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.dbeb3ddb1ce3b6231c", "query_id": "gq_95345352ba55a57d7917", "job_id": "f1d144e6b46b430fb0f1739783675a50", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/97f5cbd7-979e-4343-bc77-5b39aedacb9a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/97f5cbd7-979e-4343-bc77-5b39aedacb9a", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "f9674d5c1610b74a983ee5f6cbca74a7", "title": "Tokens-as-a-Service (Taas) Software Engineer", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, Seattle", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-27T19:55:27.406Z", "apply_url": "https://jobs.ashbyhq.com/openai/f3ddd41c-541f-485e-90d6-86c26e018e9f", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Tokens-as-a-Service (Taas) Software Engineer San Francisco, California, United States, Seattle About the Role We are seeking a Tokens-as-a-Service (TaaS) Engineer to help build the systems that convert large-scale infrastructure capacity into measurable, reliable token throughput for OpenAI workloads. In this role, you will work across performance benchmarking, tokenomics, model porting, infrastructure integration, systems tooling, and operational monitoring. You will help connect partner and first-party compute environments into OpenAI's infrastructure stack, ensuring GPU capacity can be onboarded, measured, monitored, and optimized against real workload outcomes. Key Responsibilities - Develop systems and tooling to measure, monitor, and improve token throughput across first-party and partner-owned compute environments. - Support performance benchmarking, tokenomics analysis, and model porting across heterogeneous infrastructure environments. - Build tooling to integrate external or partner infrastructure into OpenAI's internal compute, observability, and workload management systems. - Develop and monitor operational metrics including billing, usage, SLAs, utilization, reliability, and throughput. - Identify bottlenecks across hardware, networking, software, and workload enablement that prevent capacity from becoming productive tokens. - Partner with compute, infrastructure, networking, finance, and operations teams to translate raw capacity into usable workload-serving capacity. - Build dashboards, automation, and reporting systems that provide clear visibility into TaaS capacity, performance, and business outcomes. Qualifications - Strong software engineering background with experience building systems, tooling, automation, or infrastructure platforms. - Experience working across compute infrastructure, distributed systems, performance engineering, or production operations. - Ability to reason about token throughput, utilization, benchmarking, infrastructure efficiency, and workload performance. - Comfortable integrating external systems or", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.4d60f757d0c2520527", "query_id": "gq_95345352ba55a57d7917", "job_id": "f9674d5c1610b74a983ee5f6cbca74a7", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Tokens-as-a-Service (Taas) Software Engineer San Francisco, California, United States, Seattle About the Role We are seeking a Tokens-as-a-Service (TaaS) Engineer to help build the systems that convert large-scale infrastructure capacity into measurable, reliable token throughput for OpenAI workloads. In this role, you will work across performance benchmarking, tokenomics, model porting, infrastructure integration, systems tooling, and operational monitoring. You will help connect partner and first-party compute environments into OpenAI's infrastructure stack, ensuring GPU capacity can be onboarded, measured, monitored, and optimized against real workload outcomes. Key Responsibilities - Develop systems and tooling to measure, monitor, and improve token throughput across first-party and partner-owned compute environments. - Support performance benchmarking, tokenomics analysis, and model porting across heterogeneous infrastructure environments. - Build tooling to integrate external or partner infrastructure into OpenAI's internal compute, observability, and workload management systems. - Develop and monitor operational metrics including billing, usage, SLAs, utilization, reliability, and throughput. - Identify bottlenecks across hardware, networking, software, and workload enablement that prevent capacity from becoming productive tokens. - Partner with compute, infrastructure, networking, finance, and operations teams to translate raw capacity into usable workload-serving capacity. - Build dashboards, automation, and reporting systems that provide clear visibility into TaaS capacity, performance, and business outcomes. Qualifications - Strong software engineering background with experience building systems, tooling, automation, or infrastructure platforms. - Experience working across compute infrastructure, distributed systems, performance engineering, or production operations. - Ability to reason about token throughput, utilization, benchmarking, infrastructure efficiency, and workload performance. - Comfortable integrating external systems or", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f9674d5c1610b74a983ee5f6cbca74a7:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.af3ac304888723950c", "query_id": "gq_95345352ba55a57d7917", "job_id": "f9674d5c1610b74a983ee5f6cbca74a7", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:f9674d5c1610b74a983ee5f6cbca74a7:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a0d9e336574d954509", "query_id": "gq_95345352ba55a57d7917", "job_id": "f9674d5c1610b74a983ee5f6cbca74a7", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/f3ddd41c-541f-485e-90d6-86c26e018e9f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/f3ddd41c-541f-485e-90d6-86c26e018e9f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "0ba213276ac569de1b41c20fc5d436f0", "title": "Software Engineer, Productivity - Training Runtime", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-01-08T17:09:31.729Z", "apply_url": "https://jobs.ashbyhq.com/openai/c02b35b2-af37-4740-a702-2ed3b5dc3cf1", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Productivity - Training Runtime San Francisco, California, United States About the Team We're hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI's training and inference frameworks and helps execute frontier experiments. About the Role We're looking for someone who cares about the developer experience of working in and around OpenAI's core training and inference frameworks. In this role you will: - Be responsible for optimizing the development workflows of the engineers around you - Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience - Optimize iteration speed, both broadly, and in particular by optimizing specific teams' CI - Improve reliability, for instance, by driving testing strategy for particular components - Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: - You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. - You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. - When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.086db13345c9a8bc7c", "query_id": "gq_95345352ba55a57d7917", "job_id": "0ba213276ac569de1b41c20fc5d436f0", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Productivity - Training Runtime San Francisco, California, United States About the Team We're hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI's training and inference frameworks and helps execute frontier experiments. About the Role We're looking for someone who cares about the developer experience of working in and around OpenAI's core training and inference frameworks. In this role you will: - Be responsible for optimizing the development workflows of the engineers around you - Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience - Optimize iteration speed, both broadly, and in particular by optimizing specific teams' CI - Improve reliability, for instance, by driving testing strategy for particular components - Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: - You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. - You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. - When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0ba213276ac569de1b41c20fc5d436f0:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.b9bf62a7bad5bbcc53", "query_id": "gq_95345352ba55a57d7917", "job_id": "0ba213276ac569de1b41c20fc5d436f0", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0ba213276ac569de1b41c20fc5d436f0:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.0d175e1e7a4bfe99fb", "query_id": "gq_95345352ba55a57d7917", "job_id": "0ba213276ac569de1b41c20fc5d436f0", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c02b35b2-af37-4740-a702-2ed3b5dc3cf1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/c02b35b2-af37-4740-a702-2ed3b5dc3cf1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "7117f791353fa335f80c646118b441b7", "title": "Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI", "employer_name": "Scale AI", "employer_slug": "scale-ai", "location_text": "San Francisco, CA; New York, NY", "country": "US", "employment_type": "full_time", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 264800, "salary_max": 331000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 264800, "base_salary_max": 331000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50" ], "posted_at": "2026-02-10T17:09:09.000Z", "apply_url": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI San Francisco, CA; New York, NY Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale's Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you'll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle-from model and system design to evaluation, deployment, and iteration-bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: - Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. - Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. - Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "contractor_type": { "field": "contractor_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "contractor_type" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c196a98e259a7550bc", "query_id": "gq_95345352ba55a57d7917", "job_id": "7117f791353fa335f80c646118b441b7", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:7117f791353fa335f80c646118b441b7:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/scaleai/jobs/4658162005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6c5eef5eb9a497662bbb8dc26d61b7be", "title": "Senior AI Engineer, Enterprise AI", "employer_name": "GE HealthCare", "employer_slug": "ge-healthcare", "location_text": "2 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://gehc.wd5.myworkdayjobs.com/GEHC_ExternalSite/job/Remote/Senior-AI-Engineer--Enterprise-AI_R4040316-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Engineer, Enterprise AI 2 Locations posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1932393/000193239326000007/gehc-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1932393/000193239326000007/gehc-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.2439235d9c68428b4d", "query_id": "gq_95345352ba55a57d7917", "job_id": "6c5eef5eb9a497662bbb8dc26d61b7be", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:6c5eef5eb9a497662bbb8dc26d61b7be:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1932393/000193239326000007/gehc-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1932393/000193239326000007/gehc-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gehc.wd5.myworkdayjobs.com/GEHC_ExternalSite/job/Remote/Senior-AI-Engineer--Enterprise-AI_R4040316-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gehc.wd5.myworkdayjobs.com/GEHC_ExternalSite/job/Remote/Senior-AI-Engineer--Enterprise-AI_R4040316-1", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "58738db7f8a328eec2373d4181783c55", "title": "Software Engineer, Cloud Infrastructure", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2025-08-04T16:58:03.020Z", "apply_url": "https://jobs.ashbyhq.com/openai/12342ebb-dcd4-45e2-b875-fc5447fdb7d8", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Cloud Infrastructure San Francisco, California, United States About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI's technology to consumers and businesses. You'll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: - Design and build the development and production platforms that power our products, enabling reliability and security at scale - Ensure our infrastructure can scale to the next order of magnitude - Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think - Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: - Have 5+ years building core infrastructure - Have experience operating orchestration systems such as Kubernetes at scale - Have experience building abstractions over cloud platforms - Take", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.0fa02ed64bf422efe3", "query_id": "gq_95345352ba55a57d7917", "job_id": "58738db7f8a328eec2373d4181783c55", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Cloud Infrastructure San Francisco, California, United States About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI's technology to consumers and businesses. You'll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: - Design and build the development and production platforms that power our products, enabling reliability and security at scale - Ensure our infrastructure can scale to the next order of magnitude - Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think - Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: - Have 5+ years building core infrastructure - Have experience operating orchestration systems such as Kubernetes at scale - Have experience building abstractions over cloud platforms - Take", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:58738db7f8a328eec2373d4181783c55:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5c4025ba562563fc77", "query_id": "gq_95345352ba55a57d7917", "job_id": "58738db7f8a328eec2373d4181783c55", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:58738db7f8a328eec2373d4181783c55:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5ce06d1af76a54f9e5", "query_id": "gq_95345352ba55a57d7917", "job_id": "58738db7f8a328eec2373d4181783c55", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/12342ebb-dcd4-45e2-b875-fc5447fdb7d8", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/12342ebb-dcd4-45e2-b875-fc5447fdb7d8", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "51feb22160494cdfb4727d7094eeb450", "title": "Sr. Engineer - Machine Learning", "employer_name": "Magna International Inc.", "employer_slug": "magna-international", "location_text": "Maharashtra, IN", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://magna.wd3.myworkdayjobs.com/Magna/job/Maharashtra-IN/Sr-Engineer---Machine-Learning_R00231253", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Engineer - Machine Learning Maharashtra, IN posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.68f4f38110496ed754", "query_id": "gq_95345352ba55a57d7917", "job_id": "51feb22160494cdfb4727d7094eeb450", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:51feb22160494cdfb4727d7094eeb450:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1436126/000162828026016765/mg-20251231.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://magna.wd3.myworkdayjobs.com/Magna/job/Maharashtra-IN/Sr-Engineer---Machine-Learning_R00231253", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://magna.wd3.myworkdayjobs.com/Magna/job/Maharashtra-IN/Sr-Engineer---Machine-Learning_R00231253", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "97d9f9665a885f5d4238bf7bb93332c5", "title": "Software Engineer, Integrity Foundations", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2024-06-11T23:45:37.932Z", "apply_url": "https://jobs.ashbyhq.com/openai/991948b7-0305-4125-bb9a-625f5bc24189", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Integrity Foundations San Francisco, California, United States About the Team The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Applied Foundations team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability. Integrity Foundations provides the core building blocks and infrastructure for this work. About the Role At OpenAI, our mission is to advance AI in a way that is safe, reliable, and aligned with broad societal values. The applied foundations role is crucial for maintaining the trustworthiness of our platforms. You will be pivotal in developing robust defenses against a spectrum of adversarial behaviors that threaten our ecosystem. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. In this role, you will: - Develop and enhance systems to detect and prevent various forms of abuse including financial fraud, botting, and scripting. - Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. - Assist with response", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.e3636702388efa55b6", "query_id": "gq_95345352ba55a57d7917", "job_id": "97d9f9665a885f5d4238bf7bb93332c5", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer, Integrity Foundations San Francisco, California, United States About the Team The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Applied Foundations team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability. Integrity Foundations provides the core building blocks and infrastructure for this work. About the Role At OpenAI, our mission is to advance AI in a way that is safe, reliable, and aligned with broad societal values. The applied foundations role is crucial for maintaining the trustworthiness of our platforms. You will be pivotal in developing robust defenses against a spectrum of adversarial behaviors that threaten our ecosystem. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. In this role, you will: - Develop and enhance systems to detect and prevent various forms of abuse including financial fraud, botting, and scripting. - Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. - Assist with response", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:97d9f9665a885f5d4238bf7bb93332c5:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.07e19acf94fc5d9a01", "query_id": "gq_95345352ba55a57d7917", "job_id": "97d9f9665a885f5d4238bf7bb93332c5", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:97d9f9665a885f5d4238bf7bb93332c5:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a468abb7286769be83", "query_id": "gq_95345352ba55a57d7917", "job_id": "97d9f9665a885f5d4238bf7bb93332c5", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/991948b7-0305-4125-bb9a-625f5bc24189", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/991948b7-0305-4125-bb9a-625f5bc24189", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "98fabb2c248b667551daceefc03fc7a5", "title": "Machine Learning Engineer", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "2 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-08T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R167868", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer 2 Locations posted: Posted 4 Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.00a30af767ec471fcc", "query_id": "gq_95345352ba55a57d7917", "job_id": "98fabb2c248b667551daceefc03fc7a5", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:98fabb2c248b667551daceefc03fc7a5:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R167868", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R167868", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R167868", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R167868", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "29f2501748b48357e82235b3fe8662e6", "title": "Strategic Sourcing Manager, Memory Storage & CPUs", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-02-09T22:55:23.033Z", "apply_url": "https://jobs.ashbyhq.com/openai/23014bc8-37d4-4fd9-9a77-d95fdd33437f", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Strategic Sourcing Manager, Memory Storage & CPUs San Francisco, California, United States About the Team The Hardware Strategic Sourcing & Partnerships organization is responsible for the global supply of compute infrastructure powering OpenAI's model training and inference. We lead strategy, supplier engagements, commercial architecture, execution, and long-term enablement across advanced systems including custom silicon, accelerators, CPU platforms, networking, memory, power delivery, cooling, and full rack solutions. We are a small, high-impact team working across engineering, operations, finance, legal, and executive leadership to scale OpenAI's fleet worldwide. About the Role We are seeking a Sr. Strategic Sourcing Manager to own and lead sourcing strategy and global supplier partnerships for the Memory Storage & CPUs category (e.g., power systems, high-speed interconnect, memory subsystems, networking modules, mechanical enclosures, thermal systems, etc.). You will be the single-threaded leader across supplier strategy, selection, negotiations, and commercial/operational execution. You will be accountable for enabling massive growth, reducing long-term cost curves, securing supply resilience, and aligning supplier technology roadmaps with OpenAI's future system architecture needs. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities - Own the category end-to-end: strategy, business case, supplier selection, executive alignment, and operational enablement - Lead complex commercial negotiations including MSAs, NRE, cost models, open-book pricing, ramp/capacity commitments, and risk-buy frameworks - Build and scale a reliable global supply base with redundancy and geopolitical compliance, including mapping and influencing sub-tier", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "sales", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.86b61c939ce01e9046", "query_id": "gq_95345352ba55a57d7917", "job_id": "29f2501748b48357e82235b3fe8662e6", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Strategic Sourcing Manager, Memory Storage & CPUs San Francisco, California, United States About the Team The Hardware Strategic Sourcing & Partnerships organization is responsible for the global supply of compute infrastructure powering OpenAI's model training and inference. We lead strategy, supplier engagements, commercial architecture, execution, and long-term enablement across advanced systems including custom silicon, accelerators, CPU platforms, networking, memory, power delivery, cooling, and full rack solutions. We are a small, high-impact team working across engineering, operations, finance, legal, and executive leadership to scale OpenAI's fleet worldwide. About the Role We are seeking a Sr. Strategic Sourcing Manager to own and lead sourcing strategy and global supplier partnerships for the Memory Storage & CPUs category (e.g., power systems, high-speed interconnect, memory subsystems, networking modules, mechanical enclosures, thermal systems, etc.). You will be the single-threaded leader across supplier strategy, selection, negotiations, and commercial/operational execution. You will be accountable for enabling massive growth, reducing long-term cost curves, securing supply resilience, and aligning supplier technology roadmaps with OpenAI's future system architecture needs. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities - Own the category end-to-end: strategy, business case, supplier selection, executive alignment, and operational enablement - Lead complex commercial negotiations including MSAs, NRE, cost models, open-book pricing, ramp/capacity commitments, and risk-buy frameworks - Build and scale a reliable global supply base with redundancy and geopolitical compliance, including mapping and influencing sub-tier", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:29f2501748b48357e82235b3fe8662e6:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e7019b4acf2c6134b4", "query_id": "gq_95345352ba55a57d7917", "job_id": "29f2501748b48357e82235b3fe8662e6", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:29f2501748b48357e82235b3fe8662e6:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.733b429295cb4d14f9", "query_id": "gq_95345352ba55a57d7917", "job_id": "29f2501748b48357e82235b3fe8662e6", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/23014bc8-37d4-4fd9-9a77-d95fdd33437f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/23014bc8-37d4-4fd9-9a77-d95fdd33437f", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "efb2fa102be3e3dd8df561979c167743", "title": "Senior AI Agent Engineer", "employer_name": "GE Vernova", "employer_slug": "ge-vernova", "location_text": "2 Locations", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://gevernova.wd5.myworkdayjobs.com/Vernova_ExternalSite/job/Cambridge/Sr-AI-Agent-Engineer_R5025220-2", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Agent Engineer 2 Locations posted: Posted 30+ Days Ago", "parental_leave_weeks": 10, "non_birth_parent_leave_weeks": 10, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 85, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1996810/000199681026000015/gev-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1996810/000199681026000015/gev-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf", "db_column": "parental_leave_weeks", "source_url": "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Industrial", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.7d0424fee30ab96ff0", "query_id": "gq_95345352ba55a57d7917", "job_id": "efb2fa102be3e3dd8df561979c167743", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:efb2fa102be3e3dd8df561979c167743:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1996810/000199681026000015/gev-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1996810/000199681026000015/gev-20251231.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gevernova.wd5.myworkdayjobs.com/Vernova_ExternalSite/job/Cambridge/Sr-AI-Agent-Engineer_R5025220-2", "source_values": [ "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gevernova.wd5.myworkdayjobs.com/Vernova_ExternalSite/job/Cambridge/Sr-AI-Agent-Engineer_R5025220-2", "source_values": [ "https://www.gevernova.com/sustainability/documents/Sustainability/ge2022_sustainability_report_print_ada.pdf" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gevernova.wd5.myworkdayjobs.com/Vernova_ExternalSite/job/Cambridge/Sr-AI-Agent-Engineer_R5025220-2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://gevernova.wd5.myworkdayjobs.com/Vernova_ExternalSite/job/Cambridge/Sr-AI-Agent-Engineer_R5025220-2", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "69805cec826cdc13203b8f6f22ffc0d9", "title": "Systems Software Engineer, Management Plane", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": true, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-05-07T19:34:12.438Z", "apply_url": "https://jobs.ashbyhq.com/openai/21229750-8bd1-4134-a20e-2a8922b88806", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Systems Software Engineer, Management Plane San Francisco, California, United States About the Team OpenAI's Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI's supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're seeking a System Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate low-level system software for the manageability and health of OpenAI's first-party AI hardware systems. You will work across BMC, Linux, firmware interfaces, automation infra, boot and recovery, hardware diagnostics, telemetry, host and platform drivers, network software interfaces, and manufacturing and fleet readiness. A major part of this role is owning the acceptance path for partner-delivered system software: defining requirements, reviewing code and artifacts, reproducing builds, building tests, pushing fixes, and producing the evidence needed for launch decisions. This role is hands-on and high-ownership. You will write and review low-level software, debug issues across hardware and software boundaries, build infra and automation to test and manage devices in lab, guide partner deliverables, build validation evidence, and help carry platforms from bring-up through production deployment. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "relocation_assistance": { "field": "relocation_assistance", "source": "llm:greenfield:inv_371_postfix", "db_column": "relocation_assistance" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2bda72acf00f92e9f0", "query_id": "gq_95345352ba55a57d7917", "job_id": "69805cec826cdc13203b8f6f22ffc0d9", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Systems Software Engineer, Management Plane San Francisco, California, United States About the Team OpenAI's Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI's supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're seeking a System Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate low-level system software for the manageability and health of OpenAI's first-party AI hardware systems. You will work across BMC, Linux, firmware interfaces, automation infra, boot and recovery, hardware diagnostics, telemetry, host and platform drivers, network software interfaces, and manufacturing and fleet readiness. A major part of this role is owning the acceptance path for partner-delivered system software: defining requirements, reviewing code and artifacts, reproducing builds, building tests, pushing fixes, and producing the evidence needed for launch decisions. This role is hands-on and high-ownership. You will write and review low-level software, debug issues across hardware and software boundaries, build infra and automation to test and manage devices in lab, guide partner deliverables, build validation evidence, and help carry platforms from bring-up through production deployment. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:69805cec826cdc13203b8f6f22ffc0d9:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4aedb6e853d497a133", "query_id": "gq_95345352ba55a57d7917", "job_id": "69805cec826cdc13203b8f6f22ffc0d9", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:69805cec826cdc13203b8f6f22ffc0d9:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.de1edef0156556668b", "query_id": "gq_95345352ba55a57d7917", "job_id": "69805cec826cdc13203b8f6f22ffc0d9", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/21229750-8bd1-4134-a20e-2a8922b88806", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/21229750-8bd1-4134-a20e-2a8922b88806", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "relocation_assistance": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/21229750-8bd1-4134-a20e-2a8922b88806", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "1ec95d255355fa8f23dae10d4bf10794", "title": "Staff Machine Learning Engineer", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Seattle, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 201300, "salary_max": 302200, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 201300, "base_salary_max": 302200, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-04-22T20:23:51.604Z", "apply_url": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Staff Machine Learning Engineer Seattle, United States of America Join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services. We build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real-world AI applications. Our work spans the full ML lifecycle, from experimentation to deployment, and you'll play a key role in shaping how AI models are built, optimized, and scaled. We develop a platform for ML data and features that powers advanced GenAI applications. This includes embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform designed to streamline experimentation and drive innovation. We're looking for engineers and researchers passionate about generative models, data-centric ML, and intelligent systems across diverse real-world use cases. With the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production, you'll work alongside a world-class team to build intelligent, flexible systems that make ML development faster, more reliable, and more creative. The Apple Cloud AI Platform team enables Apple's next generation of intelligent products by giving Apple's ML engineers and researchers the data systems and large-scale compute they need to build and ship models at Apple's bar for quality and privacy. As a member of the Apple Cloud AI Platform team, your responsibilities will include: Design and build the platform behind Apple's", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.50103fdff34b2db816", "query_id": "gq_95345352ba55a57d7917", "job_id": "1ec95d255355fa8f23dae10d4bf10794", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:1ec95d255355fa8f23dae10d4bf10794:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200645408/staff-machine-learning-engineer?team=SFTWR", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "923d0006877d2fc3ca1b72f0fddd0274", "title": "Tokens-as-a-Service (TaaS) Lead", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, Seattle", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-27T17:30:27.118Z", "apply_url": "https://jobs.ashbyhq.com/openai/a67d16f7-0273-4052-bb48-06bf9c478eb6", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Tokens-as-a-Service (TaaS) Lead San Francisco, California, United States, Seattle About the Team OpenAI's Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy-ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will - Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. - Convert delivered power, space, and hardware capacity into production-ready token throughput. - Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. - Partner with infrastructure engineering, hardware,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b31824b533b0755c45", "query_id": "gq_95345352ba55a57d7917", "job_id": "923d0006877d2fc3ca1b72f0fddd0274", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Tokens-as-a-Service (TaaS) Lead San Francisco, California, United States, Seattle About the Team OpenAI's Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy-ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will - Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. - Convert delivered power, space, and hardware capacity into production-ready token throughput. - Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. - Partner with infrastructure engineering, hardware,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:923d0006877d2fc3ca1b72f0fddd0274:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.2e058b3169452f6c1b", "query_id": "gq_95345352ba55a57d7917", "job_id": "923d0006877d2fc3ca1b72f0fddd0274", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:923d0006877d2fc3ca1b72f0fddd0274:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.50f04435e16b74b0cd", "query_id": "gq_95345352ba55a57d7917", "job_id": "923d0006877d2fc3ca1b72f0fddd0274", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/a67d16f7-0273-4052-bb48-06bf9c478eb6", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/a67d16f7-0273-4052-bb48-06bf9c478eb6", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "06e6e1c079436df83fd9e3d53c2aaa3d", "title": "Sr. Staff Engineer (Java Fullstack or Python, AI)", "employer_name": "Experian", "employer_slug": "experian", "location_text": "Hyderabad, , India", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.smartrecruiters.com/Experian/744000127644849-sr-staff-engineer-java-fullstack-or-python-ai-", "apply_url_verified": false, "ats": "smartrecruiters", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Staff Engineer (Java Fullstack or Python, AI) Hyderabad, , India Company Description: Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description: Design and build end-to-end full stack applications (frontend, backend, APIs, data layers) Architect scalable, resilient systems using microservices and cloud-native patterns Integrate Generative AI models (LLMs) into applications for automation, insights, and user experience Build and optimize AI-driven workflows (RAG pipelines, agents, prompt engineering) Develop applications using tools like: OpenAI / Azure OpenAI / Anthropic APIs LangChain / LlamaIndex / Semantic Kernel Implement: Retrieval-Augmented Generation (RAG) Vector databases (Pinecone, Weaviate, FAISS) Embedding pipelines and semantic search Design prompt strategies and evaluation frameworks Ensure responsible AI practices (safety, bias mitigation, monitoring) Build modern UI using: React, Next.js, Angular, or Vue", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.95a9c78baad903b22e", "query_id": "gq_95345352ba55a57d7917", "job_id": "06e6e1c079436df83fd9e3d53c2aaa3d", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Staff Engineer (Java Fullstack or Python, AI) Hyderabad, , India Company Description: Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description: Design and build end-to-end full stack applications (frontend, backend, APIs, data layers) Architect scalable, resilient systems using microservices and cloud-native patterns Integrate Generative AI models (LLMs) into applications for automation, insights, and user experience Build and optimize AI-driven workflows (RAG pipelines, agents, prompt engineering) Develop applications using tools like: OpenAI / Azure OpenAI / Anthropic APIs LangChain / LlamaIndex / Semantic Kernel Implement: Retrieval-Augmented Generation (RAG) Vector databases (Pinecone, Weaviate, FAISS) Embedding pipelines and semantic search Design prompt strategies and evaluation frameworks Ensure responsible AI practices (safety, bias mitigation, monitoring) Build modern UI using: React, Next.js, Angular, or Vue", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:06e6e1c079436df83fd9e3d53c2aaa3d:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.5ac54de5bb61b9067e", "query_id": "gq_95345352ba55a57d7917", "job_id": "06e6e1c079436df83fd9e3d53c2aaa3d", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Staff Engineer (Java Fullstack or Python, AI) Hyderabad, , India Company Description: Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description: Design and build end-to-end full stack applications (frontend, backend, APIs, data layers) Architect scalable, resilient systems using microservices and cloud-native patterns Integrate Generative AI models (LLMs) into applications for automation, insights, and user experience Build and optimize AI-driven workflows (RAG pipelines, agents, prompt engineering) Develop applications using tools like: OpenAI / Azure OpenAI / Anthropic APIs LangChain / LlamaIndex / Semantic Kernel Implement: Retrieval-Augmented Generation (RAG) Vector databases (Pinecone, Weaviate, FAISS) Embedding pipelines and semantic search Design prompt strategies and evaluation frameworks Ensure responsible AI practices (safety, bias mitigation, monitoring) Build modern UI using: React, Next.js, Angular, or Vue", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.smartrecruiters.com/Experian/744000127644849-sr-staff-engineer-java-fullstack-or-python-ai-", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.smartrecruiters.com/Experian/744000127644849-sr-staff-engineer-java-fullstack-or-python-ai-", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "086a49e56c752e8a1819fd92dfd44fa9", "title": "Machine Learning Engineer", "employer_name": "CyberArk", "employer_slug": "cyberark", "location_text": "Office - USA - CA - Headquarters", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://paloaltonetworks.wd5.myworkdayjobs.com/panwexternalcareers/job/Office---USA---CA---Headquarters/Machine-Learning-Engineer_JR-010194", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer Office - USA - CA - Headquarters posted: Posted 30+ Days Ago", "parental_leave_weeks": 6, "non_birth_parent_leave_weeks": 6, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.paloaltonetworks.com/api/1.0/download/396", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 77, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.paloaltonetworks.com/api/1.0/download/396", "db_column": "parental_leave_weeks", "source_url": "https://benefits.paloaltonetworks.com/api/1.0/download/396" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.paloaltonetworks.com/api/1.0/download/396", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.paloaltonetworks.com/api/1.0/download/396" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.3e9dbb8ac2c2fd4b53", "query_id": "gq_95345352ba55a57d7917", "job_id": "086a49e56c752e8a1819fd92dfd44fa9", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:086a49e56c752e8a1819fd92dfd44fa9:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "parental_leave_weeks": { "tier": "government", "verified": true, "label": "Verified - O*NET", "source_label": "O*NET", "href": "https://benefits.paloaltonetworks.com/api/1.0/download/396", "source_values": [ "https://benefits.paloaltonetworks.com/api/1.0/download/396" ], "checked_at": "2026-06-07T00:00:00Z" }, "non_birth_parent_leave_weeks": { "tier": "government", "verified": true, "label": "Verified - O*NET", "source_label": "O*NET", "href": "https://benefits.paloaltonetworks.com/api/1.0/download/396", "source_values": [ "https://benefits.paloaltonetworks.com/api/1.0/download/396" ], "checked_at": "2026-06-07T00:00:00Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://paloaltonetworks.wd5.myworkdayjobs.com/panwexternalcareers/job/Office---USA---CA---Headquarters/Machine-Learning-Engineer_JR-010194", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://paloaltonetworks.wd5.myworkdayjobs.com/panwexternalcareers/job/Office---USA---CA---Headquarters/Machine-Learning-Engineer_JR-010194", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "9fcfaf284fcf3ba99c329638077d03af", "title": "Machine Learning Engineer - Visual Agents - Special Projects", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Cupertino, United States of America", "country": "US", "employment_type": "internship", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 126800, "salary_max": 220900, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 126800, "base_salary_max": 220900, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-04-17T19:43:34.070Z", "apply_url": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer - Visual Agents - Special Projects Cupertino, United States of America Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other's ideas stronger. The diversity of our people and their thinking inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. The Special Projects team at Apple is developing novel experiences powered by state-of-the-art agentic vision-language models that incorporate visual context into conversational interaction. We are looking for a Machine Learning Engineer to help us build, fine-tune, and rigorously evaluate these systems. A successful candidate has hands-on experience with vision-language models, knows how to translate ambiguous product requirements into measurable evaluation criteria, and is excited to work at the intersection of multimodal modeling and agentic AI. Build and evaluate vision-language agents that perceive real-world scenes and incorporate that context into conversational models Curate, annotate, and build multimodal datasets to support model training and evaluation Develop automated evaluation pipelines including LLM-as-judge frameworks, human evaluation protocols, and domain-specific benchmarks Fine-tune Large Language Models (LLMs) and Visual-Language Models (VLMs) to improve performance for specific use cases Work closely with other ML Researchers to define evaluation criteria and methodology to systematically evaluate foundation models Design controlled experiments to measure model capabilities,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.383ea9254297105381", "query_id": "gq_95345352ba55a57d7917", "job_id": "9fcfaf284fcf3ba99c329638077d03af", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:9fcfaf284fcf3ba99c329638077d03af:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200657911/machine-learning-engineer-visual-agents-special-projects?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "96105e189435a2bba4787b04c63220fd", "title": "Systems Software Engineer, Security, First Party Hardware", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": true, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-08T23:42:40.083Z", "apply_url": "https://jobs.ashbyhq.com/openai/1c48f39f-60ea-4636-87ed-8b4b4f5243e5", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Systems Software Engineer, Security, First Party Hardware San Francisco, California, United States About the Team OpenAI's Hardware organization develops silicon, systems, and platform infrastructure designed for the unique demands of advanced AI workloads. The First-Party Hardware team works across accelerators, servers, racks, firmware, manufacturing, deployment, and operations to build AI-native compute systems for OpenAI's supercomputing infrastructure. Security is a foundational property of these systems, spanning how devices are designed, provisioned, enrolled, operated, serviced, and retired. About the Role We're seeking a Security Engineer to join our First-Party Hardware team. In this role, you will own the end-to-end security foundation for OpenAI's first-party AI hardware systems, working across hardware security, embedded security, system security, and practical deployment at data center scale. You will partner with silicon, hardware, firmware, infrastructure, manufacturing, operations, and security teams to define and deliver system-level device trust. This includes boot integrity, device identity, provisioning, attestation, management-plane security, storage encryption, debug controls, firmware update and recovery, RMA, and decommissioning. You will be accountable for turning threat models into requirements, requirements into implementation, and implementation into validation evidence that can support launch decisions. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: - Own security requirements, threat models, validation strategy, and launch-readiness evidence for first-party hardware platforms from early design through production deployment. - Design and review secure boot, measured boot, roots of trust, platform firmware resilience, firmware signing, recovery, and anti-rollback strategies across heterogeneous devices. - Own device identity, provisioning, enrollment,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "relocation_assistance": { "field": "relocation_assistance", "source": "llm:greenfield:inv_371_postfix", "db_column": "relocation_assistance" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.782dc41ddb0889a4ad", "query_id": "gq_95345352ba55a57d7917", "job_id": "96105e189435a2bba4787b04c63220fd", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Systems Software Engineer, Security, First Party Hardware San Francisco, California, United States About the Team OpenAI's Hardware organization develops silicon, systems, and platform infrastructure designed for the unique demands of advanced AI workloads. The First-Party Hardware team works across accelerators, servers, racks, firmware, manufacturing, deployment, and operations to build AI-native compute systems for OpenAI's supercomputing infrastructure. Security is a foundational property of these systems, spanning how devices are designed, provisioned, enrolled, operated, serviced, and retired. About the Role We're seeking a Security Engineer to join our First-Party Hardware team. In this role, you will own the end-to-end security foundation for OpenAI's first-party AI hardware systems, working across hardware security, embedded security, system security, and practical deployment at data center scale. You will partner with silicon, hardware, firmware, infrastructure, manufacturing, operations, and security teams to define and deliver system-level device trust. This includes boot integrity, device identity, provisioning, attestation, management-plane security, storage encryption, debug controls, firmware update and recovery, RMA, and decommissioning. You will be accountable for turning threat models into requirements, requirements into implementation, and implementation into validation evidence that can support launch decisions. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: - Own security requirements, threat models, validation strategy, and launch-readiness evidence for first-party hardware platforms from early design through production deployment. - Design and review secure boot, measured boot, roots of trust, platform firmware resilience, firmware signing, recovery, and anti-rollback strategies across heterogeneous devices. - Own device identity, provisioning, enrollment,", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:96105e189435a2bba4787b04c63220fd:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.1a795472ee6e7c4603", "query_id": "gq_95345352ba55a57d7917", "job_id": "96105e189435a2bba4787b04c63220fd", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:96105e189435a2bba4787b04c63220fd:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.d273361707e19e79e3", "query_id": "gq_95345352ba55a57d7917", "job_id": "96105e189435a2bba4787b04c63220fd", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/1c48f39f-60ea-4636-87ed-8b4b4f5243e5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/1c48f39f-60ea-4636-87ed-8b4b4f5243e5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "relocation_assistance": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/1c48f39f-60ea-4636-87ed-8b4b4f5243e5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "0431412ffbb5096a0cade23a9b768c5c", "title": "AI Deployment Engineer, Public Sector - Federal Civilian", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Washington, DC, Washington, District of Columbia, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2025-09-18T17:27:47.293Z", "apply_url": "https://jobs.ashbyhq.com/openai/be7b1bf5-37ab-40f7-9ec1-e9732244f12a", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Deployment Engineer, Public Sector - Federal Civilian Washington, DC, Washington, District of Columbia, United States About the team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Government team, you'll help government agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role We are looking for a driven solutions leader with a product mindset to partner with our public sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies (federal, state, and local), policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You'll then partner with their technical teams, subject matter experts, systems integrators, and implementation partners to move from prototype through production. You'll take a holistic view of their needs and design an architecture using the OpenAI API and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Global Affairs, Applied Research, and Product teams. This role is based in Washington, DC. We offer relocation support to new employees. In this role, you will: - Deeply embed", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.df4c3d4ab0f09efd94", "query_id": "gq_95345352ba55a57d7917", "job_id": "0431412ffbb5096a0cade23a9b768c5c", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "AI Deployment Engineer, Public Sector - Federal Civilian Washington, DC, Washington, District of Columbia, United States About the team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Government team, you'll help government agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role We are looking for a driven solutions leader with a product mindset to partner with our public sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies (federal, state, and local), policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You'll then partner with their technical teams, subject matter experts, systems integrators, and implementation partners to move from prototype through production. You'll take a holistic view of their needs and design an architecture using the OpenAI API and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Global Affairs, Applied Research, and Product teams. This role is based in Washington, DC. We offer relocation support to new employees. In this role, you will: - Deeply embed", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0431412ffbb5096a0cade23a9b768c5c:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.6fb6c35333ce38eb58", "query_id": "gq_95345352ba55a57d7917", "job_id": "0431412ffbb5096a0cade23a9b768c5c", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0431412ffbb5096a0cade23a9b768c5c:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.79a4eca2b879b1594f", "query_id": "gq_95345352ba55a57d7917", "job_id": "0431412ffbb5096a0cade23a9b768c5c", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/be7b1bf5-37ab-40f7-9ec1-e9732244f12a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/be7b1bf5-37ab-40f7-9ec1-e9732244f12a", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4a0f2670479cb97098b7756775359d52", "title": "Senior Machine Learning Engineer", "employer_name": "Cresta", "employer_slug": "cresta", "location_text": "United States (Remote)", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": 205000, "salary_max": 270000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 205000, "base_salary_max": 270000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn", "a16z", "sequoia" ], "posted_at": "2025-05-29T16:38:31.000Z", "apply_url": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer United States (Remote) Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta's unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world's leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world's leading investors, including a16z, Greylock, and Sequoia. Cresta's leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences. Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta. About the role: Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs. Current focus areas include: - Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems. - Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.26ffad0326e018ac83", "query_id": "gq_95345352ba55a57d7917", "job_id": "4a0f2670479cb97098b7756775359d52", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:4a0f2670479cb97098b7756775359d52:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/cresta/jobs/4741283008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "68db85f4ede7167c578b0075bbbc9a91", "title": "Team Lead / Senior AI Engineer – AI Studio", "employer_name": "Guidehouse", "employer_slug": "guidehouse", "location_text": "IN - Chennai", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://guidehouse.wd1.myworkdayjobs.com/External/job/IN---Chennai/Team-Lead---Senior-AI-Engineer---AI-Studio_39194", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Team Lead / Senior AI Engineer – AI Studio IN - Chennai posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.ea8515a80b8cfa0988", "query_id": "gq_95345352ba55a57d7917", "job_id": "68db85f4ede7167c578b0075bbbc9a91", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:68db85f4ede7167c578b0075bbbc9a91:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://guidehouse.wd1.myworkdayjobs.com/External/job/IN---Chennai/Team-Lead---Senior-AI-Engineer---AI-Studio_39194", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://guidehouse.wd1.myworkdayjobs.com/External/job/IN---Chennai/Team-Lead---Senior-AI-Engineer---AI-Studio_39194", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "1b0ce7ff77bb25e81a8bb7c68176d97b", "title": "Head of Enterprise Sales, Korea", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Seoul, South Korea, Seoul, South Korea", "country": "KR", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-01-23T08:26:07.006Z", "apply_url": "https://jobs.ashbyhq.com/openai/d866a47d-0333-4ebf-a0d1-39c1d7edd127", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Head of Enterprise Sales, Korea Seoul, South Korea, Seoul, South Korea About the team OpenAI's mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world's best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This leadership role will be responsible for driving and implementing the overall sales strategy for OpenAI in Korea, recruiting and leading a team of sales professionals, and achieving successful deployments with our customers. The ideal candidate will possess significant sales leadership experience and a comprehensive understanding of AI technologies. This leader will have the capability to adapt to a complex and fast-changing technology environment. Responsibilities will include customer acquisition, account management, owning executive relationships, and more. This individual will also need to be a proven leader who can effectively collaborate cross-functionally with product, marketing, developer relations, operations, and core GTM teams, while guiding and mentoring a sales team towards achieving business objectives. This", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 15, "years_experience_max": null, "role_function": "sales", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.0bc98af0f5f8ac5d64", "query_id": "gq_95345352ba55a57d7917", "job_id": "1b0ce7ff77bb25e81a8bb7c68176d97b", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Head of Enterprise Sales, Korea Seoul, South Korea, Seoul, South Korea About the team OpenAI's mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world's best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This leadership role will be responsible for driving and implementing the overall sales strategy for OpenAI in Korea, recruiting and leading a team of sales professionals, and achieving successful deployments with our customers. The ideal candidate will possess significant sales leadership experience and a comprehensive understanding of AI technologies. This leader will have the capability to adapt to a complex and fast-changing technology environment. Responsibilities will include customer acquisition, account management, owning executive relationships, and more. This individual will also need to be a proven leader who can effectively collaborate cross-functionally with product, marketing, developer relations, operations, and core GTM teams, while guiding and mentoring a sales team towards achieving business objectives. This", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:1b0ce7ff77bb25e81a8bb7c68176d97b:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.144dcf24f14a0a00f4", "query_id": "gq_95345352ba55a57d7917", "job_id": "1b0ce7ff77bb25e81a8bb7c68176d97b", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:1b0ce7ff77bb25e81a8bb7c68176d97b:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.51c6f75728db9c0e35", "query_id": "gq_95345352ba55a57d7917", "job_id": "1b0ce7ff77bb25e81a8bb7c68176d97b", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d866a47d-0333-4ebf-a0d1-39c1d7edd127", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/d866a47d-0333-4ebf-a0d1-39c1d7edd127", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "2361b09b3cc9d4681469a1bc44b57f43", "title": "Solutions Engineer, Digital Natives", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "Paris, France, Paris, Île-de-France, France", "country": "FR", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-04T07:25:27.380Z", "apply_url": "https://jobs.ashbyhq.com/openai/06ec3598-8028-4a17-9654-1b2f21cbdd41", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Solutions Engineer, Digital Natives Paris, France, Paris, Île-de-France, France About the Team The Technical Success team is responsible for ensuring the safe and effective deployment of ChatGPT and OpenAI API applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, ensuring developers and enterprises maximize value from our models and products. As a Solutions Engineer, you'll help companies across industries transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are seeking an experienced pre-sales solutions engineer to partner with our Digital Natives customers and ensure they achieve tangible business value from our models through ChatGPT and the OpenAI API. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Sales, Customer Success, Security, and Product teams. This role is based in our Paris office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Deliver an exceptional pre-sales customer experience for prospects and customers by providing technical expertise, outlining the value proposition, and answering product, API, and LLM-related questions. - Demonstrate how", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "customer_success", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.54946f2515d4f9d662", "query_id": "gq_95345352ba55a57d7917", "job_id": "2361b09b3cc9d4681469a1bc44b57f43", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Solutions Engineer, Digital Natives Paris, France, Paris, Île-de-France, France About the Team The Technical Success team is responsible for ensuring the safe and effective deployment of ChatGPT and OpenAI API applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, ensuring developers and enterprises maximize value from our models and products. As a Solutions Engineer, you'll help companies across industries transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are seeking an experienced pre-sales solutions engineer to partner with our Digital Natives customers and ensure they achieve tangible business value from our models through ChatGPT and the OpenAI API. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Sales, Customer Success, Security, and Product teams. This role is based in our Paris office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Deliver an exceptional pre-sales customer experience for prospects and customers by providing technical expertise, outlining the value proposition, and answering product, API, and LLM-related questions. - Demonstrate how", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2361b09b3cc9d4681469a1bc44b57f43:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5ff1e68193afd0ab85", "query_id": "gq_95345352ba55a57d7917", "job_id": "2361b09b3cc9d4681469a1bc44b57f43", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2361b09b3cc9d4681469a1bc44b57f43:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.8bc6e95cf8dadd6a13", "query_id": "gq_95345352ba55a57d7917", "job_id": "2361b09b3cc9d4681469a1bc44b57f43", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06ec3598-8028-4a17-9654-1b2f21cbdd41", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/06ec3598-8028-4a17-9654-1b2f21cbdd41", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "0af6bc4ba872b5d95f2fddf661e35008", "title": "Principal AI Engineer", "employer_name": "RELX", "employer_slug": "relx", "location_text": "United Kingdom", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T00:00:00.000Z", "apply_url": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Principal AI Engineer United Kingdom posted: Posted 2 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.fced9fcc417ad0909a", "query_id": "gq_95345352ba55a57d7917", "job_id": "0af6bc4ba872b5d95f2fddf661e35008", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:0af6bc4ba872b5d95f2fddf661e35008:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "281c8d93c94b3bc54c0bbf669a1c8c0a", "title": "Data Scientist, Integrity Measurement", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States, New York City", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-03-05T21:59:11.726Z", "apply_url": "https://jobs.ashbyhq.com/openai/be4e1098-f7ac-46f4-babe-44ef08f47fcb", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Scientist, Integrity Measurement San Francisco, California, United States, New York City About the Team The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. Our team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability The Integrity pillar within Applied Foundations is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI's platforms. As the systems that address some of our most severe usage harms become more mature, we're adding data scientists to help us measure robustly the prevalence of these problems and the quality of our response to them. About the Role We are looking for experienced trust and safety data scientists to help us improve, productionise and monitor measurement for complex, actor- and sometimes network-level harms. A data scientist in this role will own measurement and metrics across several established harm verticals, including estimating prevalence for on-platform (and sometimes off-platform!) harm, and analyses to identify gaps and opportunities in our responses. This role is based out of our San Francisco or New York office and may involve resolving urgent escalations outside of normal work hours. Many harm areas may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 7, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3df4205964a2ac55dd", "query_id": "gq_95345352ba55a57d7917", "job_id": "281c8d93c94b3bc54c0bbf669a1c8c0a", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Data Scientist, Integrity Measurement San Francisco, California, United States, New York City About the Team The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. Our team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability The Integrity pillar within Applied Foundations is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI's platforms. As the systems that address some of our most severe usage harms become more mature, we're adding data scientists to help us measure robustly the prevalence of these problems and the quality of our response to them. About the Role We are looking for experienced trust and safety data scientists to help us improve, productionise and monitor measurement for complex, actor- and sometimes network-level harms. A data scientist in this role will own measurement and metrics across several established harm verticals, including estimating prevalence for on-platform (and sometimes off-platform!) harm, and analyses to identify gaps and opportunities in our responses. This role is based out of our San Francisco or New York office and may involve resolving urgent escalations outside of normal work hours. Many harm areas may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:281c8d93c94b3bc54c0bbf669a1c8c0a:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.539133070d856bb62d", "query_id": "gq_95345352ba55a57d7917", "job_id": "281c8d93c94b3bc54c0bbf669a1c8c0a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:281c8d93c94b3bc54c0bbf669a1c8c0a:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.65026a24e968544c67", "query_id": "gq_95345352ba55a57d7917", "job_id": "281c8d93c94b3bc54c0bbf669a1c8c0a", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/be4e1098-f7ac-46f4-babe-44ef08f47fcb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/be4e1098-f7ac-46f4-babe-44ef08f47fcb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/be4e1098-f7ac-46f4-babe-44ef08f47fcb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2b7866e52c4719fd8a1b615ef5c5a4f6", "title": "Senior Manager, Transfer Pricing", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-06-08T22:57:20.672Z", "apply_url": "https://jobs.ashbyhq.com/openai/98b712b7-4e53-4c5f-abb4-3cd0cd865b1c", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Manager, Transfer Pricing San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Tax team is a vital part of OpenAI, ensuring compliance with tax laws and regulations while optimizing the company's tax position. We work closely with various departments to provide tax insights and strategies that support the company's growth and financial objectives. About the Role: This role will support transfer pricing initiatives and other strategic transactions by advising on risks. In parallel, the role will serve as a core tax advisor to the business on transfer pricing matters, including business expansion, operating model, transfer pricing considerations and the tax aspects of commercial and intercompany arrangements. The Transfer Pricing Senior Manager will partner closely with Legal, Finance, Corporate Development, and commercial teams to ensure tax positions are technically sound, operationally executable, and aligned with business and compliance requirements. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Lead the design, development, and implementation of comprehensive global transfer pricing strategies and policies. - Oversee preparation of transfer pricing documentation and compliance, including master files, local files, and country-by-country reports, across multiple jurisdictions and coordinate with local tax teams. - Draft and manage intercompany agreements. - Support transfer pricing aspects of business initiatives. - Evaluate APAs and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.24b6b1e8d282eb58e7", "query_id": "gq_95345352ba55a57d7917", "job_id": "2b7866e52c4719fd8a1b615ef5c5a4f6", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Manager, Transfer Pricing San Francisco, California, United States About the Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Tax team is a vital part of OpenAI, ensuring compliance with tax laws and regulations while optimizing the company's tax position. We work closely with various departments to provide tax insights and strategies that support the company's growth and financial objectives. About the Role: This role will support transfer pricing initiatives and other strategic transactions by advising on risks. In parallel, the role will serve as a core tax advisor to the business on transfer pricing matters, including business expansion, operating model, transfer pricing considerations and the tax aspects of commercial and intercompany arrangements. The Transfer Pricing Senior Manager will partner closely with Legal, Finance, Corporate Development, and commercial teams to ensure tax positions are technically sound, operationally executable, and aligned with business and compliance requirements. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Lead the design, development, and implementation of comprehensive global transfer pricing strategies and policies. - Oversee preparation of transfer pricing documentation and compliance, including master files, local files, and country-by-country reports, across multiple jurisdictions and coordinate with local tax teams. - Draft and manage intercompany agreements. - Support transfer pricing aspects of business initiatives. - Evaluate APAs and", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2b7866e52c4719fd8a1b615ef5c5a4f6:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.87870e9bb0758d0421", "query_id": "gq_95345352ba55a57d7917", "job_id": "2b7866e52c4719fd8a1b615ef5c5a4f6", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:2b7866e52c4719fd8a1b615ef5c5a4f6:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a709870ece3775306d", "query_id": "gq_95345352ba55a57d7917", "job_id": "2b7866e52c4719fd8a1b615ef5c5a4f6", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/98b712b7-4e53-4c5f-abb4-3cd0cd865b1c", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/98b712b7-4e53-4c5f-abb4-3cd0cd865b1c", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "90afe0ff30a78fd6e4b42ecf0e35426b", "title": "Senior Machine Learning Engineer", "employer_name": "Trulia", "employer_slug": "trulia", "location_text": "Remote-USA", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://zillow.wd5.myworkdayjobs.com/Zillow_Group_External/job/Remote-USA/Senior-Machine-Learning-Engineer_P750067-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer Remote-USA posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 48, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.d6d35ceea45f233c7f", "query_id": "gq_95345352ba55a57d7917", "job_id": "90afe0ff30a78fd6e4b42ecf0e35426b", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:90afe0ff30a78fd6e4b42ecf0e35426b:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zillow.wd5.myworkdayjobs.com/Zillow_Group_External/job/Remote-USA/Senior-Machine-Learning-Engineer_P750067-1", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zillow.wd5.myworkdayjobs.com/Zillow_Group_External/job/Remote-USA/Senior-Machine-Learning-Engineer_P750067-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://zillow.wd5.myworkdayjobs.com/Zillow_Group_External/job/Remote-USA/Senior-Machine-Learning-Engineer_P750067-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "7779491d52294cf236b0fe964c61d418", "title": "Sr Machine Learning Engineer", "employer_name": "Amgen", "employer_slug": "amgen", "location_text": "India - Hyderabad", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://amgen.wd1.myworkdayjobs.com/Careers/job/India---Hyderabad/Sr-Machine-Learning-Engineer_R-216773", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr Machine Learning Engineer India - Hyderabad posted: Posted 30+ Days Ago", "parental_leave_weeks": 6, "non_birth_parent_leave_weeks": 6, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 52, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/318154/000031815426000010/amgn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/318154/000031815426000010/amgn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads", "db_column": "parental_leave_weeks", "source_url": "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Healthcare", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.69840230d5752179a4", "query_id": "gq_95345352ba55a57d7917", "job_id": "7779491d52294cf236b0fe964c61d418", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:7779491d52294cf236b0fe964c61d418:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/318154/000031815426000010/amgn-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/318154/000031815426000010/amgn-20251231.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://amgen.wd1.myworkdayjobs.com/Careers/job/India---Hyderabad/Sr-Machine-Learning-Engineer_R-216773", "source_values": [ "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads" ], "checked_at": "2026-06-07T00:00:00Z" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://amgen.wd1.myworkdayjobs.com/Careers/job/India---Hyderabad/Sr-Machine-Learning-Engineer_R-216773", "source_values": [ "https://www.amgen.com/stories/2019/07/unique-benefits---family-leave-policy-provides-time-off-for-new-dads" ], "checked_at": "2026-06-07T00:00:00Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://amgen.wd1.myworkdayjobs.com/Careers/job/India---Hyderabad/Sr-Machine-Learning-Engineer_R-216773", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://amgen.wd1.myworkdayjobs.com/Careers/job/India---Hyderabad/Sr-Machine-Learning-Engineer_R-216773", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } }, { "id": "34f401ce08a18d5ccff4b6fe9f707f37", "title": "Strategic Finance, Compute", "employer_name": "OpenAI", "employer_slug": "openai", "location_text": "San Francisco, California, United States", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cnbc_disruptor50", "cbinsights_unicorn", "a16z", "sequoia", "foundersfund" ], "posted_at": "2026-04-21T18:29:06.926Z", "apply_url": "https://jobs.ashbyhq.com/openai/b4196174-9cc3-487d-9d21-848bc283b80f", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Strategic Finance, Compute San Francisco, California, United States About the Team The Compute & Infrastructure Strategy team handles strategy and execution of OpenAI's compute roadmap. This team's key responsibilities span financial analysis & reporting, capacity planning, commercial and business development, and strategic partnerships. We partner across the business to allocate and deploy our resources for the highest impact outcomes. About the Role Compute is a key lever for OpenAI and AI progress. We are seeking a Strategic Finance Compute Lead to provide finance leadership for our compute and infrastructure spend and play a significant role in shaping our long-term compute strategy. You will play a critical role developing financial models for all areas of compute, analyzing spend patterns, and providing critical insights to optimize and plan for our future compute needs. This role will be a key partner to our scaling and supercomputing engineering teams providing financial expertise and guidance to optimize our capacity investments and drive strategic decision-making, while collaborating with other members of the finance organization to align our compute strategy with broader financial considerations. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and develop financial models across different elements of compute (GPUs, CPUs, storage and networking) - Lead strategic financial analysis for long-term capacity initiatives, working closely with scaling and supercomputing engineering teams - Maintain deep expertise on compute", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3ad0feb028e90a37f4", "query_id": "gq_95345352ba55a57d7917", "job_id": "34f401ce08a18d5ccff4b6fe9f707f37", "signal_type": "query_match", "display_text": "Description: \"openai\"", "tooltip": "Description matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Strategic Finance, Compute San Francisco, California, United States About the Team The Compute & Infrastructure Strategy team handles strategy and execution of OpenAI's compute roadmap. This team's key responsibilities span financial analysis & reporting, capacity planning, commercial and business development, and strategic partnerships. We partner across the business to allocate and deploy our resources for the highest impact outcomes. About the Role Compute is a key lever for OpenAI and AI progress. We are seeking a Strategic Finance Compute Lead to provide finance leadership for our compute and infrastructure spend and play a significant role in shaping our long-term compute strategy. You will play a critical role developing financial models for all areas of compute, analyzing spend patterns, and providing critical insights to optimize and plan for our future compute needs. This role will be a key partner to our scaling and supercomputing engineering teams providing financial expertise and guidance to optimize our capacity investments and drive strategic decision-making, while collaborating with other members of the finance organization to align our compute strategy with broader financial considerations. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and develop financial models across different elements of compute (GPUs, CPUs, storage and networking) - Lead strategic financial analysis for long-term capacity initiatives, working closely with scaling and supercomputing engineering teams - Maintain deep expertise on compute", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:34f401ce08a18d5ccff4b6fe9f707f37:description:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.67ac998fd700de6f04", "query_id": "gq_95345352ba55a57d7917", "job_id": "34f401ce08a18d5ccff4b6fe9f707f37", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer matched \"openai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_95345352ba55a57d7917:34f401ce08a18d5ccff4b6fe9f707f37:employer:openai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.c5324fc2c10fec8a93", "query_id": "gq_95345352ba55a57d7917", "job_id": "34f401ce08a18d5ccff4b6fe9f707f37", "signal_type": "query_match", "display_text": "Employer: \"openai\"", "tooltip": "Employer contains \"openai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "OpenAI", "matched_input": "openai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/b4196174-9cc3-487d-9d21-848bc283b80f", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/b4196174-9cc3-487d-9d21-848bc283b80f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/openai/b4196174-9cc3-487d-9d21-848bc283b80f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } } ], "total": 1999, "page": 6, "per_page": 100, "applied_filters": { "q": "OpenAI" }, "hidden_unknown_benefits_count": 0, "hidden_quality_floor_count": 0, "quality_floor": "default", "search_profile": { "profile_id": "inv382.d6.pg_textsearch_bge_small_rrf.v1", "bm25_extension": "pg_textsearch", "vector_model": "BAAI/bge-small-en-v1.5", "vector_model_version": "v1.5", "fusion_method": "rrf" }, "explanation_context": { "non_trivial_query": false, "query_terms": [ "openai" ], "active_filter_keys": [], "visible_signal_limit": 3, "visible_trust_limit": 2 }, "event_context": { "query_context": { "query_id": "50ae0ffd-ff4a-49dc-8554-4191509c728d", "issued_at": "2026-08-12T21:51:11.977Z", "route": "/jobs", "page": 6, "per_page": 100, "total_results": 1999, "sort": "relevance", "ranking_policy": "hybrid_rrf_rerank", "ranking_policy_version": "inv382.jobs.search.v2", "query_hash": "hmac_sha256:MEn1oImFmNO6cZGBIe4G9DABT--huAbqA0LhiNtMxpA", "filter_hash": "hmac_sha256:6CBErDPXOFVCSNkSGbTmuw6GxoMjwSLro0KqZMtxL_0", "query_features": { "has_q": true, "q_term_count": 1, "q_length_bucket": "1_15", "q_pii_redacted": false, "state_count": 0, "benefit_filters": [], "quality_floor": "default" }, "exposures": [ { "result_id": "b52f2f0e53b69701d582ad2e96cd2a34", "position": 501, "page_position": 1, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28564868654914455, "rrf_score": 0.0029069767441860465, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "9c0364f8da8f0d0242a01fc1199beb85", "position": 502, "page_position": 2, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002898550724637681, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 167, "quality_score": 45 } }, { "result_id": "2a0d4e872c20738376b4d4c02ddff7f0", "position": 503, "page_position": 3, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28565840210566384, "rrf_score": 0.002890173410404624, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 77, "quality_score": 35 } }, { "result_id": "a30aa7faa7d80c0ebf74118aaf862168", "position": 504, "page_position": 4, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002881844380403458, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 85, "quality_score": 55 } }, { "result_id": "2f47bf5e9464f9cd3bfcbe11370a0efc", "position": 505, "page_position": 5, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28566424336050367, "rrf_score": 0.002881844380403458, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "7b67a2115e7a0f82884335689329ca90", "position": 506, "page_position": 6, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2857132809503885, "rrf_score": 0.0028735632183908046, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "4b50e6d67aefce5c9b3e0334924144f2", "position": 507, "page_position": 7, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2857849427589796, "rrf_score": 0.0028653295128939827, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "68b6bcbdeaa9213a4cab774b8dc99817", "position": 508, "page_position": 8, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2858925291363865, "rrf_score": 0.002857142857142857, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 79, "quality_score": 35 } }, { "result_id": "f8d50ff792a24484d0eb4949d80e0151", "position": 509, "page_position": 9, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2858982511819439, "rrf_score": 0.002849002849002849, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 65, "quality_score": 35 } }, { "result_id": "9a0631f0c31f405762dc0c3e524e2bd2", "position": 510, "page_position": 10, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28590075457687525, "rrf_score": 0.002840909090909091, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "0d23a5d9a26309b4548ed82246120b2b", "position": 511, "page_position": 11, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28593719005584717, "rrf_score": 0.0028328611898017, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "b8fbfe196169d9d4e3ae64e7950aa391", "position": 512, "page_position": 12, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0028328611898017, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 135, "quality_score": 45 } }, { "result_id": "1a47df1ec92e118fb42fb810884e5ad2", "position": 513, "page_position": 13, "retrieval_features": { "bm25_score": 0, "vector_score": 0.285963773727417, "rrf_score": 0.0028169014084507044, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 116, "quality_score": 55 } }, { "result_id": "bc88b6bcfc214d0be75be4bb9ea48022", "position": 514, "page_position": 14, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0028169014084507044, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 71, "quality_score": 45 } }, { "result_id": "8d11cf5daf99298b3abf4bd99b72f7b9", "position": 515, "page_position": 15, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2860051393508911, "rrf_score": 0.0028089887640449437, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "c1eda52968d4e0082eb8984357052bfa", "position": 516, "page_position": 16, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0028011204481792717, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 64, "quality_score": 55 } }, { "result_id": "c4d24032b3c5036300a337938f357516", "position": 517, "page_position": 17, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002793296089385475, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 71, "quality_score": 45 } }, { "result_id": "4726baf3b54b1e27a669b1b83610bd60", "position": 518, "page_position": 18, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28607654571533203, "rrf_score": 0.002793296089385475, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 144, "quality_score": 45 } }, { "result_id": "c5d26f6953bd5786dd7bd753eefc047b", "position": 519, "page_position": 19, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002785515320334262, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 88, "quality_score": 55 } }, { "result_id": "043a740c0e33d89fd4254f9b7c7d5d79", "position": 520, "page_position": 20, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28610031091568877, "rrf_score": 0.002785515320334262, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 114, "quality_score": 45 } }, { "result_id": "a09fcb803a97a42e6a0a4b9c0277849b", "position": 521, "page_position": 21, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2861853837966919, "rrf_score": 0.002777777777777778, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "4aa97308ff0a58574e68d67961734ac7", "position": 522, "page_position": 22, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28626038350226657, "rrf_score": 0.002770083102493075, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 71, "quality_score": 35 } }, { "result_id": "3cd1b85b9da42431b293486b74efd121", "position": 523, "page_position": 23, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28629231452941895, "rrf_score": 0.0027624309392265192, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "d02bda6ededa6ce8c78774b509b82758", "position": 524, "page_position": 24, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0027624309392265192, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 152, "quality_score": 45 } }, { "result_id": "1f94da0556f1d66f8997769ccbe9781e", "position": 525, "page_position": 25, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2862975597381592, "rrf_score": 0.0027548209366391185, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 79, "quality_score": 35 } }, { "result_id": "48515ffd85ae7079a9e9883df24087a4", "position": 526, "page_position": 26, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28631460666656494, "rrf_score": 0.0027472527472527475, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 138, "quality_score": 55 } }, { "result_id": "9478389ec219ad4374a646e3dc664cdb", "position": 527, "page_position": 27, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2863361664810069, "rrf_score": 0.0027397260273972603, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "d5072abde348461552d486096690c193", "position": 528, "page_position": 28, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0027397260273972603, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 418, "quality_score": 45 } }, { "result_id": "d6ad0f9416485eff7ae08349ca1330fd", "position": 529, "page_position": 29, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.00273224043715847, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 77, "quality_score": 55 } }, { "result_id": "e3e88a147ba05ad4b57007cd56ac958d", "position": 530, "page_position": 30, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28638438663575605, "rrf_score": 0.0027247956403269754, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "ecf88e2ab95c6b92434ec67b4fc6cf58", "position": 531, "page_position": 31, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0027247956403269754, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 295, "quality_score": 45 } }, { "result_id": "f0eef7ed710e5cf3e63a6e5766190455", "position": 532, "page_position": 32, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002717391304347826, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 141, "quality_score": 45 } }, { "result_id": "3845efd2e53739d6da37a177e9dc69ef", "position": 533, "page_position": 33, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28642868995666504, "rrf_score": 0.002717391304347826, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 133, "quality_score": 55 } }, { "result_id": "7b7d57a676335e1e6ab9c3aa0c0e0fa4", "position": 534, "page_position": 34, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2864699959754944, "rrf_score": 0.0027100271002710027, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 68, "quality_score": 35 } }, { "result_id": "f29822143a874d8c68d9aa49ece92917", "position": 535, "page_position": 35, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0027100271002710027, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 98, "quality_score": 45 } }, { "result_id": "f46c48de72a4c33354608d1835d01c93", "position": 536, "page_position": 36, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002702702702702703, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 610, "quality_score": 45 } }, { "result_id": "c3028c2222edfacd89efc2d8cbab5f3f", "position": 537, "page_position": 37, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2864832878112793, "rrf_score": 0.002702702702702703, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "f70f2444cafb8fc93a1f748d5a441864", "position": 538, "page_position": 38, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0026954177897574125, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 77, "quality_score": 45 } }, { "result_id": "83200813f077e695eb3f3b573c46c336", "position": 539, "page_position": 39, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2865493893623352, "rrf_score": 0.002688172043010753, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "f7644461e36cbc58104f0c0c642a297a", "position": 540, "page_position": 40, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002688172043010753, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 114, "quality_score": 45 } }, { "result_id": "492dbe6ff953ed4d76fb28aaae7ef652", "position": 541, "page_position": 41, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28657732267908187, "rrf_score": 0.002680965147453083, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "f939d22c42fcd198bff2a224abc7e1a2", "position": 542, "page_position": 42, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.002680965147453083, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 72, "quality_score": 45 } }, { "result_id": "d89157d0193acb21e1c3c96f914ba71b", "position": 543, "page_position": 43, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2865867614746094, "rrf_score": 0.00267379679144385, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 133, "quality_score": 55 } }, { "result_id": "fe1ece3469192982cc42bca636fc01df", "position": 544, "page_position": 44, "retrieval_features": { "bm25_score": -8.055632591247559, "vector_score": 0, "rrf_score": 0.0026666666666666666, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 65, "quality_score": 45 } }, { "result_id": "2a1c293273db1f9147137cdf7abbecae", "position": 545, "page_position": 45, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28677332401275635, "rrf_score": 0.0026595744680851063, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "07954639a6e38d2a55e2ece8fe0c5917", "position": 546, "page_position": 46, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0026595744680851063, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 111, "quality_score": 45 } }, { "result_id": "18e0bb8d4d165e00adcb2dc6b657bb4e", "position": 547, "page_position": 47, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002652519893899204, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 69, "quality_score": 45 } }, { "result_id": "85c0d262549b7cb423d0d8110d653eb1", "position": 548, "page_position": 48, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28680557012557983, "rrf_score": 0.002652519893899204, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 69, "quality_score": 35 } }, { "result_id": "231c09057f842d3ead8ac6dcd7c722ed", "position": 549, "page_position": 49, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0026455026455026454, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 190, "quality_score": 45 } }, { "result_id": "b5d1ea58e0c163c4a7eba5449dfb39e0", "position": 550, "page_position": 50, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28693169355392456, "rrf_score": 0.002638522427440633, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "30804f7131cb27927bfa9fce7eeda365", "position": 551, "page_position": 51, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002631578947368421, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 45 } }, { "result_id": "56bfcfa7b8c91578cfcc2a859740eeed", "position": 552, "page_position": 52, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28706960159125194, "rrf_score": 0.002631578947368421, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 84, "quality_score": 35 } }, { "result_id": "4f1295b35d1df9294582ed8c89cdecf5", "position": 553, "page_position": 53, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2871110439300537, "rrf_score": 0.0026246719160104987, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 61, "quality_score": 35 } }, { "result_id": "3f281a8e3defb3a7b29942654dd78b33", "position": 554, "page_position": 54, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002617801047120419, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 81, "quality_score": 55 } }, { "result_id": "4a2bd9d540a4bd84e4f154ee85575847", "position": 555, "page_position": 55, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2872028350830078, "rrf_score": 0.0026109660574412533, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 368, "quality_score": 55 } }, { "result_id": "f5865cccf8f990ee0e4edcd2bd70c3b2", "position": 556, "page_position": 56, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28720651345214043, "rrf_score": 0.0026041666666666665, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "957da3183383480963b4f6ac12eb4a97", "position": 557, "page_position": 57, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0026041666666666665, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 191, "quality_score": 45 } }, { "result_id": "188c196e449ded279f543b784f07464a", "position": 558, "page_position": 58, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2872128486633301, "rrf_score": 0.0025974025974025974, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 61, "quality_score": 55 } }, { "result_id": "9ed5b654b737ac0839463c0d08b50878", "position": 559, "page_position": 59, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0025974025974025974, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 485, "quality_score": 45 } }, { "result_id": "aa9b1dec57aee5edd2456525cc78907a", "position": 560, "page_position": 60, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0025906735751295338, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 114, "quality_score": 45 } }, { "result_id": "78315604d123257de6a462223d8f5766", "position": 561, "page_position": 61, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28734834714819946, "rrf_score": 0.0025906735751295338, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 237, "quality_score": 45 } }, { "result_id": "a6d9cba0714096d91583d3b88c74cbad", "position": 562, "page_position": 62, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28735095262527466, "rrf_score": 0.002583979328165375, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "b005dfb165c163b612c939f9ed5e2860", "position": 563, "page_position": 63, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002577319587628866, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 79, "quality_score": 45 } }, { "result_id": "bc47ed3da8fa450a9e8ef22d4e96a14a", "position": 564, "page_position": 64, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002570694087403599, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 76, "quality_score": 45 } }, { "result_id": "0a5272e841127b6f88debe0640507e88", "position": 565, "page_position": 65, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2873722698501425, "rrf_score": 0.002570694087403599, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 138, "quality_score": 55 } }, { "result_id": "10010c1655808cbafcbbc203600a3fba", "position": 566, "page_position": 66, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28746289014816284, "rrf_score": 0.002564102564102564, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 133, "quality_score": 55 } }, { "result_id": "d08737666c166b15bd285e8bac8b5efe", "position": 567, "page_position": 67, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0025575447570332483, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 76, "quality_score": 45 } }, { "result_id": "e00cfdf065c48759cc1f2c03f7194d33", "position": 568, "page_position": 68, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28749072551727295, "rrf_score": 0.0025575447570332483, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 488, "quality_score": 55 } }, { "result_id": "e351198ff317f65fc81cd48511624d34", "position": 569, "page_position": 69, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002551020408163265, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 85, "quality_score": 45 } }, { "result_id": "61463a707ebf5cca6d4c21111cb34630", "position": 570, "page_position": 70, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2875357098856133, "rrf_score": 0.002551020408163265, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "56acd2f33bfe80093e10f24c869d012d", "position": 571, "page_position": 71, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2875402398383462, "rrf_score": 0.002544529262086514, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 121, "quality_score": 45 } }, { "result_id": "f1d144e6b46b430fb0f1739783675a50", "position": 572, "page_position": 72, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.0025380710659898475, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 148, "quality_score": 45 } }, { "result_id": "f9674d5c1610b74a983ee5f6cbca74a7", "position": 573, "page_position": 73, "retrieval_features": { "bm25_score": -7.866351127624512, "vector_score": 0, "rrf_score": 0.002531645569620253, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 107, "quality_score": 45 } }, { "result_id": "0ba213276ac569de1b41c20fc5d436f0", "position": 574, "page_position": 74, "retrieval_features": { "bm25_score": -7.709527969360352, "vector_score": 0, "rrf_score": 0.0025252525252525255, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 216, "quality_score": 45 } }, { "result_id": "7117f791353fa335f80c646118b441b7", "position": 575, "page_position": 75, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28757057860072854, "rrf_score": 0.0025252525252525255, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 183, "quality_score": 55 } }, { "result_id": "6c5eef5eb9a497662bbb8dc26d61b7be", "position": 576, "page_position": 76, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28759753704071045, "rrf_score": 0.0025188916876574307, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "58738db7f8a328eec2373d4181783c55", "position": 577, "page_position": 77, "retrieval_features": { "bm25_score": -7.709527969360352, "vector_score": 0, "rrf_score": 0.0025188916876574307, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 373, "quality_score": 45 } }, { "result_id": "51feb22160494cdfb4727d7094eeb450", "position": 578, "page_position": 78, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28760647773742676, "rrf_score": 0.002506265664160401, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "97d9f9665a885f5d4238bf7bb93332c5", "position": 579, "page_position": 79, "retrieval_features": { "bm25_score": -7.709527969360352, "vector_score": 0, "rrf_score": 0.0024937655860349127, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 791, "quality_score": 45 } }, { "result_id": "98fabb2c248b667551daceefc03fc7a5", "position": 580, "page_position": 80, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28774694873410644, "rrf_score": 0.0024875621890547263, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 65, "quality_score": 35 } }, { "result_id": "29f2501748b48357e82235b3fe8662e6", "position": 581, "page_position": 81, "retrieval_features": { "bm25_score": -7.685760498046875, "vector_score": 0, "rrf_score": 0.0024875621890547263, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 183, "quality_score": 45 } }, { "result_id": "efb2fa102be3e3dd8df561979c167743", "position": 582, "page_position": 82, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28782719373703003, "rrf_score": 0.0024813895781637717, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "69805cec826cdc13203b8f6f22ffc0d9", "position": 583, "page_position": 83, "retrieval_features": { "bm25_score": -7.685760498046875, "vector_score": 0, "rrf_score": 0.0024813895781637717, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 97, "quality_score": 45 } }, { "result_id": "1ec95d255355fa8f23dae10d4bf10794", "position": 584, "page_position": 84, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28784269094467163, "rrf_score": 0.0024752475247524753, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 112, "quality_score": 55 } }, { "result_id": "923d0006877d2fc3ca1b72f0fddd0274", "position": 585, "page_position": 85, "retrieval_features": { "bm25_score": -7.685760498046875, "vector_score": 0, "rrf_score": 0.0024752475247524753, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 107, "quality_score": 45 } }, { "result_id": "06e6e1c079436df83fd9e3d53c2aaa3d", "position": 586, "page_position": 86, "retrieval_features": { "bm25_score": -7.513275146484375, "vector_score": 0, "rrf_score": 0.0024691358024691358, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 45 } }, { "result_id": "086a49e56c752e8a1819fd92dfd44fa9", "position": 587, "page_position": 87, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28785645961761475, "rrf_score": 0.0024691358024691358, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "9fcfaf284fcf3ba99c329638077d03af", "position": 588, "page_position": 88, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2879222631454468, "rrf_score": 0.0024630541871921183, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 117, "quality_score": 55 } }, { "result_id": "96105e189435a2bba4787b04c63220fd", "position": 589, "page_position": 89, "retrieval_features": { "bm25_score": -7.513275146484375, "vector_score": 0, "rrf_score": 0.0024630541871921183, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 64, "quality_score": 45 } }, { "result_id": "0431412ffbb5096a0cade23a9b768c5c", "position": 590, "page_position": 90, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.002457002457002457, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 328, "quality_score": 45 } }, { "result_id": "4a0f2670479cb97098b7756775359d52", "position": 591, "page_position": 91, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28794509172439575, "rrf_score": 0.002457002457002457, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 440, "quality_score": 55 } }, { "result_id": "68db85f4ede7167c578b0075bbbc9a91", "position": 592, "page_position": 92, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2880029082298279, "rrf_score": 0.0024449877750611247, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "1b0ce7ff77bb25e81a8bb7c68176d97b", "position": 593, "page_position": 93, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.0024449877750611247, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 201, "quality_score": 45 } }, { "result_id": "2361b09b3cc9d4681469a1bc44b57f43", "position": 594, "page_position": 94, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.0024390243902439024, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 69, "quality_score": 45 } }, { "result_id": "0af6bc4ba872b5d95f2fddf661e35008", "position": 595, "page_position": 95, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28814399242401123, "rrf_score": 0.0024330900243309003, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 63, "quality_score": 35 } }, { "result_id": "281c8d93c94b3bc54c0bbf669a1c8c0a", "position": 596, "page_position": 96, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.0024330900243309003, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 159, "quality_score": 45 } }, { "result_id": "2b7866e52c4719fd8a1b615ef5c5a4f6", "position": 597, "page_position": 97, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.0024271844660194173, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 64, "quality_score": 45 } }, { "result_id": "90afe0ff30a78fd6e4b42ecf0e35426b", "position": 598, "page_position": 98, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28817641735076904, "rrf_score": 0.0024271844660194173, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "7779491d52294cf236b0fe964c61d418", "position": 599, "page_position": 99, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28823643922805786, "rrf_score": 0.002421307506053269, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 92, "quality_score": 35 } }, { "result_id": "34f401ce08a18d5ccff4b6fe9f707f37", "position": 600, "page_position": 100, "retrieval_features": { "bm25_score": -7.479862689971924, "vector_score": 0, "rrf_score": 0.002421307506053269, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 113, "quality_score": 45 } } ] }, "context_signature": "LQMZs8FntVtb7vocesppDd9wErJMD9BXl5ES6scsBTA", "event_token": "LQMZs8FntVtb7vocesppDd9wErJMD9BXl5ES6scsBTA" } }