{ "results": [ { "id": "667d3c7603f1831234a2766c6e146364", "title": "Supplier Development Engineer (R4621)", "employer_name": "Shield AI", "employer_slug": "shield-ai", "location_text": "Taipei", "country": "TW", "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": "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": 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" ], "posted_at": "2026-03-31T16:04:22.187Z", "apply_url": "https://jobs.lever.co/shieldai/34d71878-2793-427c-ac43-e83cff4a5fee", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Supplier Development Engineer (R4621) Taipei Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: We are seeking a highly skilled and motivated Supplier Development Engineer to join Shield AI. The ideal candidate will have a strong background in supplier development, quality engineering, production process improvement, and supply chain management within the aerospace industry. This role is critical in enhancing supplier performance by solving supplier challenges that impact quality/on-time delivery/scaling, supporting the onboarding of suppliers to new designs, and delivering on our mission to deliver affordable and autonomous mass at scale. Job Description: We are seeking a highly skilled and motivated Supplier Development Engineer to join Shield AI. The ideal candidate will have a strong background in supplier development, quality engineering, production process improvement, and supply chain management within the aerospace industry. This role is critical in enhancing supplier performance by solving supplier challenges that impact quality/on-time delivery/scaling, supporting the onboarding of suppliers to new designs, and delivering on our mission to deliver affordable and autonomous mass at scale. Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems.", "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" }, "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": 7, "years_experience_max": 11, "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": 50, "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": [], "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.lever.co/shieldai/34d71878-2793-427c-ac43-e83cff4a5fee", "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/shieldai/34d71878-2793-427c-ac43-e83cff4a5fee", "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.lever.co/shieldai/34d71878-2793-427c-ac43-e83cff4a5fee", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "81195ca11e9844db22b1d7b18c22f9c0", "title": "Machine Learning Research Engineer, 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": "2025-10-31T18:10:48.000Z", "apply_url": "https://job-boards.greenhouse.io/scaleai/jobs/4625344005", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Research Engineer, Agents - Enterprise GenAI San Francisco, CA; New York, NY AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As an Agent MLRE, you will be working on applying our Agent RL Training + Building algorithms to real life enterprise datasets across our clients + benchmarks. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you! You will: - Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. - Research cutting edge algorithms to integrate directly into our training stack. - Build agents that leverage our proprietary agent-building algorithms to automatically hill climb datasets - including defining highly performant", "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" }, "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" }, "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" }, "assessment_required": { "field": "assessment_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "assessment_required" } }, "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": "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": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.bfd26f965f9aced94b", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "81195ca11e9844db22b1d7b18c22f9c0", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:81195ca11e9844db22b1d7b18c22f9c0: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/4625344005", "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/4625344005", "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/4625344005", "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/4625344005", "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/4625344005", "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/4625344005", "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/4625344005", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6ca6185906c7bfd954fb16046f103ec8", "title": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch", "employer_name": "Google", "employer_slug": "google", "location_text": "Mountain View, CA, USA", "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": 163000, "salary_max": 237000, "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": 163000, "base_salary_max": 237000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu" ], "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": "2026-06-10T15:37:54.000Z", "apply_url": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "apply_url_verified": false, "ats": "google_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch Mountain View, CA, USA A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Google Pixel Watch team focuses on designing and delivering the world's most helpful wearable experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global wearables and create transformative experiences for users across the world. The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world. Individual pay is determined by factors including job-related", "parental_leave_weeks": 18, "non_birth_parent_leave_weeks": 18, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 94, "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" }, "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-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/1652044/000165204426000018/goog-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://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "parental_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" } }, "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": "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": 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.697eda069d53892ad1", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "6ca6185906c7bfd954fb16046f103ec8", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch Mountain View, CA, USA A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Google Pixel Watch team focuses on designing and delivering the world's most helpful wearable experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global wearables and create transformative experiences for users across the world. The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world. Individual pay is determined by factors including job-related", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:6ca6185906c7bfd954fb16046f103ec8:description:intelligence", "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.a3f5d98b709bb874dc", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "6ca6185906c7bfd954fb16046f103ec8", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch Mountain View, CA, USA A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Google Pixel Watch team focuses on designing and delivering the world's most helpful wearable experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global wearables and create transformative experiences for users across the world. The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world. Individual pay is determined by factors including job-related", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:6ca6185906c7bfd954fb16046f103ec8:description:solve", "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.56b95e764663516135", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "6ca6185906c7bfd954fb16046f103ec8", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch Mountain View, CA, USA A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Google Pixel Watch team focuses on designing and delivering the world's most helpful wearable experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global wearables and create transformative experiences for users across the world. The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world. Individual pay is determined by factors including job-related", "matched_input": "solve", "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.query.description_excerpt.b417bac63b9fd6c02c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "6ca6185906c7bfd954fb16046f103ec8", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Technical Program Manager III, Hardware Platform Architecture, Pixel Watch Mountain View, CA, USA A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Google Pixel Watch team focuses on designing and delivering the world's most helpful wearable experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global wearables and create transformative experiences for users across the world. The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world. Individual pay is determined by factors including job-related", "matched_input": "intelligence", "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": "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": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "source_values": [ "llm:greenfield:inv_371_postfix" ], "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/1652044/000165204426000018/goog-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "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.google.com/about/careers/applications/signin?jobId=CiUAL2FckTd4ve8_FHvT7PzLCk78VtVlb_kWzzO72T0Mz6TtAuyEEjsACxwdTH7NLl6HKstzeAndZtOfO_TPZpDdVqQWdsEXtzGPaY6fE7xLfBxxraI5lBC5Zg-_EWySrcHk8Q%3D%3D_V2&loc=US&title=Technical+Program+Manager+III", "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": "1fe389a0d581b088e203c44d68ea618a", "title": "Staff Machine Learning Engineer", "employer_name": "Databricks", "employer_slug": "databricks", "location_text": "San Francisco, California", "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": 190000, "salary_max": 285000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "ote", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 190000, "base_salary_max": 285000, "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": 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" ], "posted_at": "2026-02-02T22:44:35.000Z", "apply_url": "https://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Staff Machine Learning Engineer San Francisco, California P-1504 The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we've launched Databricks Assistant , AI/BI Genie , and Agent Bricks working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others. As our GenAI products continue to evolve, we are seeking multiple GenAI Engineers from junior levels to more senior levels to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale. Key Responsibilities - Shape the direction of our applied AI areas and intelligence features in our products . Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie). - Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains. - Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration. - Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": 12, "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" }, "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" }, "bonus_offered": { "field": "bonus_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "bonus_offered" }, "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" }, "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" }, "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" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" } }, "seniority": "staff_plus", "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": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "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": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.fcf28fc5f6ddd1ca2e", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "1fe389a0d581b088e203c44d68ea618a", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Staff Machine Learning Engineer San Francisco, California P-1504 The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we've launched Databricks Assistant , AI/BI Genie , and Agent Bricks working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others. As our GenAI products continue to evolve, we are seeking multiple GenAI Engineers from junior levels to more senior levels to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale. Key Responsibilities - Shape the direction of our applied AI areas and intelligence features in our products . Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie). - Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains. - Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration. - Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user", "matched_input": "intelligence", "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.d3a6b16230b1b2c697", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "1fe389a0d581b088e203c44d68ea618a", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:1fe389a0d581b088e203c44d68ea618a: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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "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://databricks.com/company/careers/open-positions/job?gh_jid=8401114002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4770131f4485a891b740b620e038e638", "title": "Research Scientist, Robotics, Embodied AI, DeepMind", "employer_name": "DeepMind", "employer_slug": "deepmind", "location_text": "Mountain View, CA, USA", "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": 147000, "salary_max": 211000, "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": 147000, "base_salary_max": 211000, "salary_disclosed": true, "equity_included": true, "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": "2026-06-04T15:08:22.000Z", "apply_url": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "apply_url_verified": false, "ats": "google_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Research Scientist, Robotics, Embodied AI, DeepMind Mountain View, CA, USA We believe there are many problems in the world in which robotics could play a significant role in making it easier, faster and safer for people to get things done. We're looking for roboticists, designers, hardware and software engineers to help us explore these possibilities, develop breakthrough technologies, and build new products that could help millions of people. At DeepMind Robotics we are pioneering bringing AI to the physical world. We are powering an era of physical agents, enabling robots to perceive, plan, think, use tools, and act to better solve tasks. In this role, you will develop Vision Language Action (VLA) models that combine Gemini's world understanding with physical actions to directly control robots. You will include Gemini Robotics (our Gemini model for the physical world), and Gemini Robotics On-Device (our Gemini model that runs without a data network). You will also develop reasoning and agentic systems for the physical world, including Gemini Robotics-ER, a Gemini agent with spatial understanding. You will enable robots to perform a range of tasks, respond interactively to their environment, achieve dexterity, and reason over long multi-step tasks. You will focus on advancing in areas of general purpose robotics, including real world understanding, action generalization, human robot interaction, whole-body control, and continual learning. Additionally, you will partner with robotics companies to bring this intelligence to applications at scale. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a", "parental_leave_weeks": 18, "non_birth_parent_leave_weeks": 18, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 94, "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": "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" }, "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" }, "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" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "parental_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" } }, "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": 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.ae74a51500297d6420", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "4770131f4485a891b740b620e038e638", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Research Scientist, Robotics, Embodied AI, DeepMind Mountain View, CA, USA We believe there are many problems in the world in which robotics could play a significant role in making it easier, faster and safer for people to get things done. We're looking for roboticists, designers, hardware and software engineers to help us explore these possibilities, develop breakthrough technologies, and build new products that could help millions of people. At DeepMind Robotics we are pioneering bringing AI to the physical world. We are powering an era of physical agents, enabling robots to perceive, plan, think, use tools, and act to better solve tasks. In this role, you will develop Vision Language Action (VLA) models that combine Gemini's world understanding with physical actions to directly control robots. You will include Gemini Robotics (our Gemini model for the physical world), and Gemini Robotics On-Device (our Gemini model that runs without a data network). You will also develop reasoning and agentic systems for the physical world, including Gemini Robotics-ER, a Gemini agent with spatial understanding. You will enable robots to perform a range of tasks, respond interactively to their environment, achieve dexterity, and reason over long multi-step tasks. You will focus on advancing in areas of general purpose robotics, including real world understanding, action generalization, human robot interaction, whole-body control, and continual learning. Additionally, you will partner with robotics companies to bring this intelligence to applications at scale. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a", "matched_input": "intelligence", "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.query.description_excerpt.bfe4dfc90049c82a6a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "4770131f4485a891b740b620e038e638", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Research Scientist, Robotics, Embodied AI, DeepMind Mountain View, CA, USA We believe there are many problems in the world in which robotics could play a significant role in making it easier, faster and safer for people to get things done. We're looking for roboticists, designers, hardware and software engineers to help us explore these possibilities, develop breakthrough technologies, and build new products that could help millions of people. At DeepMind Robotics we are pioneering bringing AI to the physical world. We are powering an era of physical agents, enabling robots to perceive, plan, think, use tools, and act to better solve tasks. In this role, you will develop Vision Language Action (VLA) models that combine Gemini's world understanding with physical actions to directly control robots. You will include Gemini Robotics (our Gemini model for the physical world), and Gemini Robotics On-Device (our Gemini model that runs without a data network). You will also develop reasoning and agentic systems for the physical world, including Gemini Robotics-ER, a Gemini agent with spatial understanding. You will enable robots to perform a range of tasks, respond interactively to their environment, achieve dexterity, and reason over long multi-step tasks. You will focus on advancing in areas of general purpose robotics, including real world understanding, action generalization, human robot interaction, whole-body control, and continual learning. Additionally, you will partner with robotics companies to bring this intelligence to applications at scale. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a", "matched_input": "solve", "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.4f835f8a45aec853a5", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "4770131f4485a891b740b620e038e638", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:4770131f4485a891b740b620e038e638: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": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "source_values": [ "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckQpFyCqW3nIHT9aA1sg6WL2fBdc1uJ1iApABvQQsEBx7EjsACxwdTK3_2ZHCRHY_Rvd9MZCRMeJxkJXR-lrlIMtQBlFZ5uuKJ8bYNER81VNL2MJPmAx3R734ZRvklw%3D%3D_V2&loc=US&title=Research+Scientist", "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": "748e4c1f937210339d133ad03c265913", "title": "Deployments Software Engineer", "employer_name": "Physical Intelligence", "employer_slug": "physical-intelligence", "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": 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": 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": [ "cbinsights_unicorn", "sequoia" ], "posted_at": "2026-06-08T13:11:12.814Z", "apply_url": "https://jobs.ashbyhq.com/physicalintelligence/1e8a741a-d415-4c34-9ac8-eda4c5393e41", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Deployments Software Engineer San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. Deploying robots into the real world takes more than a capable model - it takes designing a physical system that's fast, safe, and reliable enough to run unattended on a customer's floor, backed by software you can observe, debug, and trust if something goes wrong. As a Robotics Software Engineer, you'll build that system. You'll integrate state-of-the-art models with robots that work on-site - building system safeguards, the teleoperation interfaces operators rely on, and the latency optimizations that make remote control feel instant. You'll work with researchers, platform engineers, and robot operators to make the whole stack dependable enough that customers bet their operations on it. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Design remote teleoperation interfaces: Develop", "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" }, "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.62f3bda5963cd67e8a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "748e4c1f937210339d133ad03c265913", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Deployments Software Engineer San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. Deploying robots into the real world takes more than a capable model - it takes designing a physical system that's fast, safe, and reliable enough to run unattended on a customer's floor, backed by software you can observe, debug, and trust if something goes wrong. As a Robotics Software Engineer, you'll build that system. You'll integrate state-of-the-art models with robots that work on-site - building system safeguards, the teleoperation interfaces operators rely on, and the latency optimizations that make remote control feel instant. You'll work with researchers, platform engineers, and robot operators to make the whole stack dependable enough that customers bet their operations on it. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Design remote teleoperation interfaces: Develop", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:748e4c1f937210339d133ad03c265913:description:solve", "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.c6fdacca11c5915b80", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "748e4c1f937210339d133ad03c265913", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Deployments Software Engineer San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. Deploying robots into the real world takes more than a capable model - it takes designing a physical system that's fast, safe, and reliable enough to run unattended on a customer's floor, backed by software you can observe, debug, and trust if something goes wrong. As a Robotics Software Engineer, you'll build that system. You'll integrate state-of-the-art models with robots that work on-site - building system safeguards, the teleoperation interfaces operators rely on, and the latency optimizations that make remote control feel instant. You'll work with researchers, platform engineers, and robot operators to make the whole stack dependable enough that customers bet their operations on it. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Design remote teleoperation interfaces: Develop", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:748e4c1f937210339d133ad03c265913:description:intelligence", "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.5b19f9e90a0a998ff2", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "748e4c1f937210339d133ad03c265913", "signal_type": "query_match", "display_text": "Employer: \"intelligence\"", "tooltip": "Employer matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Physical Intelligence", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:748e4c1f937210339d133ad03c265913:employer:intelligence", "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.f087d6935650f53130", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "748e4c1f937210339d133ad03c265913", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Deployments Software Engineer San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. Deploying robots into the real world takes more than a capable model - it takes designing a physical system that's fast, safe, and reliable enough to run unattended on a customer's floor, backed by software you can observe, debug, and trust if something goes wrong. As a Robotics Software Engineer, you'll build that system. You'll integrate state-of-the-art models with robots that work on-site - building system safeguards, the teleoperation interfaces operators rely on, and the latency optimizations that make remote control feel instant. You'll work with researchers, platform engineers, and robot operators to make the whole stack dependable enough that customers bet their operations on it. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Design remote teleoperation interfaces: Develop", "matched_input": "solve", "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.query.employer_name.56125edf14486b9c43", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "748e4c1f937210339d133ad03c265913", "signal_type": "query_match", "display_text": "Employer: \"intelligence\"", "tooltip": "Employer contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Physical Intelligence", "matched_input": "intelligence", "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 } } ], "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": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/physicalintelligence/1e8a741a-d415-4c34-9ac8-eda4c5393e41", "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/physicalintelligence/1e8a741a-d415-4c34-9ac8-eda4c5393e41", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "750f04b38cdbd1265375b443615ddc6a", "title": "Customer Engineer, Business Intelligence, Google Cloud", "employer_name": "Google", "employer_slug": "google", "location_text": "London, UK", "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": true, "equity_included_source": null, "equity_type": [ "rsu" ], "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": "2026-05-28T21:38:40.000Z", "apply_url": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "apply_url_verified": false, "ats": "google_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Customer Engineer, Business Intelligence, Google Cloud London, UK As a Customer Engineer (CE) with a specialty in Looker BI, you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of specialized workloads. You will leverage your deep expertise in our product areas, in partnership with Platform CEs, to develop architectures and prototypes, proofs-of-concept, and demos to promote new, highly specialized solutions to customers. You will solve customer issues and provide a critical feedback loop to influence customers and product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Serve as the Looker subject matter expert alongside Sales teams to differentiate Google Cloud and recommend scalable, trusted data experiences that drive innovation. Design and deliver tailored presentations, demonstrations, and technical prototypes that clearly articulate specific use cases and business value to customers. Lead technical proof-of-concepts and", "parental_leave_weeks": 18, "non_birth_parent_leave_weeks": 18, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "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": "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.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/1652044/000165204426000018/goog-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "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" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "parental_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 6, "years_experience_max": 10, "role_function": "data", "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": 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": 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.query.description_excerpt.59e5e7ae765efa3fee", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "750f04b38cdbd1265375b443615ddc6a", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Customer Engineer, Business Intelligence, Google Cloud London, UK As a Customer Engineer (CE) with a specialty in Looker BI, you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of specialized workloads. You will leverage your deep expertise in our product areas, in partnership with Platform CEs, to develop architectures and prototypes, proofs-of-concept, and demos to promote new, highly specialized solutions to customers. You will solve customer issues and provide a critical feedback loop to influence customers and product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Serve as the Looker subject matter expert alongside Sales teams to differentiate Google Cloud and recommend scalable, trusted data experiences that drive innovation. Design and deliver tailored presentations, demonstrations, and technical prototypes that clearly articulate specific use cases and business value to customers. Lead technical proof-of-concepts and", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:750f04b38cdbd1265375b443615ddc6a:description:intelligence", "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.e1f93e1a24037e685e", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "750f04b38cdbd1265375b443615ddc6a", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Customer Engineer, Business Intelligence, Google Cloud London, UK As a Customer Engineer (CE) with a specialty in Looker BI, you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of specialized workloads. You will leverage your deep expertise in our product areas, in partnership with Platform CEs, to develop architectures and prototypes, proofs-of-concept, and demos to promote new, highly specialized solutions to customers. You will solve customer issues and provide a critical feedback loop to influence customers and product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Serve as the Looker subject matter expert alongside Sales teams to differentiate Google Cloud and recommend scalable, trusted data experiences that drive innovation. Design and deliver tailored presentations, demonstrations, and technical prototypes that clearly articulate specific use cases and business value to customers. Lead technical proof-of-concepts and", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:750f04b38cdbd1265375b443615ddc6a:description:solve", "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.title.dd6dd0711f81dbd122", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "750f04b38cdbd1265375b443615ddc6a", "signal_type": "query_match", "display_text": "Title: \"intelligence\"", "tooltip": "Title matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Customer Engineer, Business Intelligence, Google Cloud", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:750f04b38cdbd1265375b443615ddc6a:title:intelligence", "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.8ffae5918811faaa84", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "750f04b38cdbd1265375b443615ddc6a", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Customer Engineer, Business Intelligence, Google Cloud London, UK As a Customer Engineer (CE) with a specialty in Looker BI, you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of specialized workloads. You will leverage your deep expertise in our product areas, in partnership with Platform CEs, to develop architectures and prototypes, proofs-of-concept, and demos to promote new, highly specialized solutions to customers. You will solve customer issues and provide a critical feedback loop to influence customers and product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Serve as the Looker subject matter expert alongside Sales teams to differentiate Google Cloud and recommend scalable, trusted data experiences that drive innovation. Design and deliver tailored presentations, demonstrations, and technical prototypes that clearly articulate specific use cases and business value to customers. Lead technical proof-of-concepts and", "matched_input": "solve", "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.query.title.4dac56653e0b28857a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "750f04b38cdbd1265375b443615ddc6a", "signal_type": "query_match", "display_text": "Title: \"intelligence\"", "tooltip": "Title contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Customer Engineer, Business Intelligence, Google Cloud", "matched_input": "intelligence", "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": "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/1652044/000165204426000018/goog-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "source_values": [ "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/" ], "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "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://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckSiXWECvjQaBT0gx6vQ0kCQLLc51V_JR5UhPXd9J9ZyNEjsACxwdTGT2Rkmod2dcdagb3Kl2QcbhOQLwbAbfbGsqKhLaC7Rw8bAOxqBMLNNBtu2hAS_WpcY-Utmyiw%3D%3D_V2&loc=GB&title=Customer+Engineer", "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": "2da15a86a76fbb5ef9866580acaa5e8a", "title": "AI Engineering Director", "employer_name": "Clearpoint Neuro", "employer_slug": "clearpoint-neuro", "location_text": "Auckland, New Zealand", "country": "NZ", "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": "2026-06-04T16:41:40.000Z", "apply_url": "https://jobs.lever.co/clearpoint/0aeda7e6-1e3c-4835-85f5-150f4611c624", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineering Director Auckland, New Zealand", "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/1285550/000119312526111231/clpt-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/1285550/000119312526111231/clpt-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": "Healthcare", "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.ad1e6fc1538472b685", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "2da15a86a76fbb5ef9866580acaa5e8a", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:2da15a86a76fbb5ef9866580acaa5e8a: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/1285550/000119312526111231/clpt-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1285550/000119312526111231/clpt-20251231.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/clearpoint/0aeda7e6-1e3c-4835-85f5-150f4611c624", "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.lever.co/clearpoint/0aeda7e6-1e3c-4835-85f5-150f4611c624", "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": "753112db9514c9ca09a27c440e97bebf", "title": "Senior AI Solutions Engineer", "employer_name": "Fiserv", "employer_slug": "fiserv", "location_text": "6 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": "2026-05-26T00:00:00.000Z", "apply_url": "https://fiserv.wd5.myworkdayjobs.com/EXT/job/Berkeley-Heights-New-Jersey/Senior-AI-Solutions-Engineer_R-10389066", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Solutions Engineer 6 Locations posted: Posted 17 Days Ago", "parental_leave_weeks": 12, "non_birth_parent_leave_weeks": 2, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.pdf", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 69, "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/798354/000079835426000009/fi-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/798354/000079835426000009/fi-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.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.pdf", "db_column": "parental_leave_weeks", "source_url": "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.pdf" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.pdf", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.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": "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.7df1e370b83d911021", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "753112db9514c9ca09a27c440e97bebf", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:753112db9514c9ca09a27c440e97bebf: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": "Employer benefits source", "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/798354/000079835426000009/fi-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/798354/000079835426000009/fi-20251231.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://fiserv.wd5.myworkdayjobs.com/EXT/job/Berkeley-Heights-New-Jersey/Senior-AI-Solutions-Engineer_R-10389066", "source_values": [ "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.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://fiserv.wd5.myworkdayjobs.com/EXT/job/Berkeley-Heights-New-Jersey/Senior-AI-Solutions-Engineer_R-10389066", "source_values": [ "https://www.fiserv.com/content/dam/fiserv-ent/final-files/marketing-collateral/documents-handouts-flyers/2024-csr-report-0425.pdf" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://fiserv.wd5.myworkdayjobs.com/EXT/job/Berkeley-Heights-New-Jersey/Senior-AI-Solutions-Engineer_R-10389066", "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://fiserv.wd5.myworkdayjobs.com/EXT/job/Berkeley-Heights-New-Jersey/Senior-AI-Solutions-Engineer_R-10389066", "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": "762d40d6a2b63762b5b6f6e4f7fb264b", "title": "Applied Researcher", "employer_name": "Physical Intelligence", "employer_slug": "physical-intelligence", "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": 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": 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": [ "cbinsights_unicorn", "sequoia" ], "posted_at": "2026-01-23T05:30:53.269Z", "apply_url": "https://jobs.ashbyhq.com/physicalintelligence/1a7a181f-c318-4e0b-9516-c7111b3e3968", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied Researcher San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware). - Train and tune policies, curate data, and iterate to improve real-world performance. - Write production-quality code that interfaces with Pi's infrastructure. - Work with operators to set up tests, evals, and data collection pipelines. - Engage with partners to understand use cases and observe robots in deployment contexts. - Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers. - Define and shape a vision for what real-world deployments will look like in the long-term What We Hope You'll Bring", "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" }, "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": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.49617b48b98c39a64c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Applied Researcher San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware). - Train and tune policies, curate data, and iterate to improve real-world performance. - Write production-quality code that interfaces with Pi's infrastructure. - Work with operators to set up tests, evals, and data collection pipelines. - Engage with partners to understand use cases and observe robots in deployment contexts. - Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers. - Define and shape a vision for what real-world deployments will look like in the long-term What We Hope You'll Bring", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:762d40d6a2b63762b5b6f6e4f7fb264b:description:intelligence", "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.dbcc42f586c2163daf", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Applied Researcher San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware). - Train and tune policies, curate data, and iterate to improve real-world performance. - Write production-quality code that interfaces with Pi's infrastructure. - Work with operators to set up tests, evals, and data collection pipelines. - Engage with partners to understand use cases and observe robots in deployment contexts. - Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers. - Define and shape a vision for what real-world deployments will look like in the long-term What We Hope You'll Bring", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:762d40d6a2b63762b5b6f6e4f7fb264b:description:solve", "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.8ec4944125033be68b", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "signal_type": "query_match", "display_text": "Employer: \"intelligence\"", "tooltip": "Employer matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Physical Intelligence", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:762d40d6a2b63762b5b6f6e4f7fb264b:employer:intelligence", "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.1e5b4b2170d3afee5b", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Applied Researcher San Francisco, California, United States Who We Are Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future. The Team The Deployments team is responsible for solving real world problems with our models and robots. We tackle the full problem space: integrating with customer workflows, training models to solve their dexterous tasks, and ensuring the on-site reliability of the system. This breadth of problem space is why we're a full-stack robotics team - whether it's thinking about customer facing experiences or fine-tuning models for tasks no robot has done before, we put forth the best solution Pi has to offer. In This Role You Will - Deploy and debug learned policies on physical robots, diagnosing failures across the full stack (perception, policy, control, hardware). - Train and tune policies, curate data, and iterate to improve real-world performance. - Write production-quality code that interfaces with Pi's infrastructure. - Work with operators to set up tests, evals, and data collection pipelines. - Engage with partners to understand use cases and observe robots in deployment contexts. - Bridge research and operations: translate research advances into deployable systems, and surface real-world failure modes back to researchers and (software and hardware!) engineers. - Define and shape a vision for what real-world deployments will look like in the long-term What We Hope You'll Bring", "matched_input": "solve", "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.query.employer_name.d79da4f7b78c4d943a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "signal_type": "query_match", "display_text": "Employer: \"intelligence\"", "tooltip": "Employer contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Physical Intelligence", "matched_input": "intelligence", "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 } } ], "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": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/physicalintelligence/1a7a181f-c318-4e0b-9516-c7111b3e3968", "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/physicalintelligence/1a7a181f-c318-4e0b-9516-c7111b3e3968", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "7f7733c05f35b03648123d75bfa74186", "title": "Business Intelligence Engineer, Supply Chain Data Science", "employer_name": "Amazon", "employer_slug": "amazon", "location_text": "Mexico City, Mexico City, MEX", "country": "MX", "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": "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": [ "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": true, "childcare_subsidy": true, "fertility_family_building_benefits": true, "adoption_assistance_offered": true, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-02-18T00:00:00.000Z", "apply_url": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "apply_url_verified": false, "ats": "amazon_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Business Intelligence Engineer, Supply Chain Data Science Mexico City, Mexico City, MEX Are you a data enthusiast? Does the world's most complex logistic systems inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need tomorrow. Amazon's extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon's data and generate actionable recommendations using optimization and simulation. Come build with us! This role will collaborate with diverse set of stakeholder including product managers, program managers, data scientists, software development engineers and other partner teams to analyze large data sets, prove and disprove hypothesis, automate existing solutions and build self-service dashboards and reports. Key job responsibilities E2E design and creation of data pipelines including harmonization of different data sources (Data base, API,", "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.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "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": "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.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/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "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.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "db_column": "parental_leave_weeks", "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" }, "mental_health_support": { "field": "mental_health_support", "source": "llm:greenfield:inv_371_postfix", "db_column": "mental_health_support" }, "adoption_assistance_offered": { "field": "adoption_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "adoption_assistance_offered" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" }, "fertility_family_building_benefits": { "field": "fertility_family_building_benefits", "source": "llm:greenfield:inv_371_postfix", "db_column": "fertility_family_building_benefits" } }, "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": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Industrial", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "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": true, "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.14223ecf4b832968ee", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7f7733c05f35b03648123d75bfa74186", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Business Intelligence Engineer, Supply Chain Data Science Mexico City, Mexico City, MEX Are you a data enthusiast? Does the world's most complex logistic systems inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need tomorrow. Amazon's extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon's data and generate actionable recommendations using optimization and simulation. Come build with us! This role will collaborate with diverse set of stakeholder including product managers, program managers, data scientists, software development engineers and other partner teams to analyze large data sets, prove and disprove hypothesis, automate existing solutions and build self-service dashboards and reports. Key job responsibilities E2E design and creation of data pipelines including harmonization of different data sources (Data base, API,", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:7f7733c05f35b03648123d75bfa74186:description:intelligence", "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.c8bcebb9ef2c433efd", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7f7733c05f35b03648123d75bfa74186", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Business Intelligence Engineer, Supply Chain Data Science Mexico City, Mexico City, MEX Are you a data enthusiast? Does the world's most complex logistic systems inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need tomorrow. Amazon's extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon's data and generate actionable recommendations using optimization and simulation. Come build with us! This role will collaborate with diverse set of stakeholder including product managers, program managers, data scientists, software development engineers and other partner teams to analyze large data sets, prove and disprove hypothesis, automate existing solutions and build self-service dashboards and reports. Key job responsibilities E2E design and creation of data pipelines including harmonization of different data sources (Data base, API,", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:7f7733c05f35b03648123d75bfa74186:description:solve", "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.title.cb776c5a00aca8c7e2", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7f7733c05f35b03648123d75bfa74186", "signal_type": "query_match", "display_text": "Title: \"intelligence\"", "tooltip": "Title matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Business Intelligence Engineer, Supply Chain Data Science", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:7f7733c05f35b03648123d75bfa74186:title:intelligence", "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.29f3b4f57e7667437a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7f7733c05f35b03648123d75bfa74186", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Business Intelligence Engineer, Supply Chain Data Science Mexico City, Mexico City, MEX Are you a data enthusiast? Does the world's most complex logistic systems inspire your curiosity? Is your passion to navigate through hundreds of systems, processes, and data sources to solve the puzzles and identify the next big opportunity? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need tomorrow. Amazon's extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon's data and generate actionable recommendations using optimization and simulation. Come build with us! This role will collaborate with diverse set of stakeholder including product managers, program managers, data scientists, software development engineers and other partner teams to analyze large data sets, prove and disprove hypothesis, automate existing solutions and build self-service dashboards and reports. Key job responsibilities E2E design and creation of data pipelines including harmonization of different data sources (Data base, API,", "matched_input": "solve", "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.query.title.0fc062246950547530", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7f7733c05f35b03648123d75bfa74186", "signal_type": "query_match", "display_text": "Title: \"intelligence\"", "tooltip": "Title contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Business Intelligence Engineer, Supply Chain Data Science", "matched_input": "intelligence", "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": "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": { "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "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/1018724/000101872426000004/amzn-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" ], "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://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "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://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "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://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "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://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "fertility_family_building_benefits": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "mental_health_support": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "adoption_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3184440/business-intelligence-engineer-supply-chain-data-science", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" } } }, { "id": "7d935599600945ad12c23778190f5d56", "title": "Solution Architect", "employer_name": "Neural Magic", "employer_slug": "neural-magic", "location_text": "Mumbai", "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": [ "a16z" ], "posted_at": "2026-05-13T00:00:00.000Z", "apply_url": "https://redhat.wd5.myworkdayjobs.com/jobs/job/Mumbai/Solution-Architect_R-052980-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Solution Architect Mumbai 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": 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": "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": 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.0cd8e7be4300850e96", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "7d935599600945ad12c23778190f5d56", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:7d935599600945ad12c23778190f5d56: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://redhat.wd5.myworkdayjobs.com/jobs/job/Mumbai/Solution-Architect_R-052980-1", "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://redhat.wd5.myworkdayjobs.com/jobs/job/Mumbai/Solution-Architect_R-052980-1", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "8d73779c519091de59b4f1de5a99def1", "title": "Senior Autonomy Engineer - Deep Learning", "employer_name": "Skydio", "employer_slug": "skydio", "location_text": "San Mateo, California, United States, San Mateo, California, United States", "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": 170000, "salary_max": 277500, "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": 170000, "base_salary_max": 277500, "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" ], "posted_at": "2025-12-15T23:29:42.231Z", "apply_url": "https://jobs.ashbyhq.com/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Autonomy Engineer - Deep Learning San Mateo, California, United States, San Mateo, California, United States Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond . About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about solving open-end problems in object detection and tracking, motion prediction, flow estimation, and total scene understanding, while leveraging massive amounts of structured video data, we would love to hear from you. How you'll make an impact: - Design and implement deep learning solutions that solve detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones - Leverage state-of-the-art methods in unsupervised learning, few shot learning, and foundational models for data efficient ML - Curate and enhance synthetic data that powers our deep learning algorithms along with massive amounts of structured video data - Refine and optimize models for low-latency on embedded hardware - Characterize and quantify the performance of the vision systems - Research", "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" }, "equity_type": { "field": "equity_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "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" }, "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" }, "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": "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": true, "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.18a4b4ba6d29ea938d", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "8d73779c519091de59b4f1de5a99def1", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Autonomy Engineer - Deep Learning San Mateo, California, United States, San Mateo, California, United States Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond . About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about solving open-end problems in object detection and tracking, motion prediction, flow estimation, and total scene understanding, while leveraging massive amounts of structured video data, we would love to hear from you. How you'll make an impact: - Design and implement deep learning solutions that solve detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones - Leverage state-of-the-art methods in unsupervised learning, few shot learning, and foundational models for data efficient ML - Curate and enhance synthetic data that powers our deep learning algorithms along with massive amounts of structured video data - Refine and optimize models for low-latency on embedded hardware - Characterize and quantify the performance of the vision systems - Research", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:8d73779c519091de59b4f1de5a99def1:description:solve", "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.eecdb0545adab1500c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "8d73779c519091de59b4f1de5a99def1", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Autonomy Engineer - Deep Learning San Mateo, California, United States, San Mateo, California, United States Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond . About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about solving open-end problems in object detection and tracking, motion prediction, flow estimation, and total scene understanding, while leveraging massive amounts of structured video data, we would love to hear from you. How you'll make an impact: - Design and implement deep learning solutions that solve detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones - Leverage state-of-the-art methods in unsupervised learning, few shot learning, and foundational models for data efficient ML - Curate and enhance synthetic data that powers our deep learning algorithms along with massive amounts of structured video data - Refine and optimize models for low-latency on embedded hardware - Characterize and quantify the performance of the vision systems - Research", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:8d73779c519091de59b4f1de5a99def1:description:intelligence", "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.563f060829d6df0c29", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "8d73779c519091de59b4f1de5a99def1", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Senior Autonomy Engineer - Deep Learning San Mateo, California, United States, San Mateo, California, United States Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond . About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about solving open-end problems in object detection and tracking, motion prediction, flow estimation, and total scene understanding, while leveraging massive amounts of structured video data, we would love to hear from you. How you'll make an impact: - Design and implement deep learning solutions that solve detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones - Leverage state-of-the-art methods in unsupervised learning, few shot learning, and foundational models for data efficient ML - Curate and enhance synthetic data that powers our deep learning algorithms along with massive amounts of structured video data - Refine and optimize models for low-latency on embedded hardware - Characterize and quantify the performance of the vision systems - Research", "matched_input": "intelligence", "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.query.description_excerpt.668904f969c4821446", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "8d73779c519091de59b4f1de5a99def1", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Senior Autonomy Engineer - Deep Learning San Mateo, California, United States, San Mateo, California, United States Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond . About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about solving open-end problems in object detection and tracking, motion prediction, flow estimation, and total scene understanding, while leveraging massive amounts of structured video data, we would love to hear from you. How you'll make an impact: - Design and implement deep learning solutions that solve detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones - Leverage state-of-the-art methods in unsupervised learning, few shot learning, and foundational models for data efficient ML - Curate and enhance synthetic data that powers our deep learning algorithms along with massive amounts of structured video data - Refine and optimize models for low-latency on embedded hardware - Characterize and quantify the performance of the vision systems - Research", "matched_input": "solve", "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 } } ], "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://jobs.ashbyhq.com/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "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/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "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/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "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/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "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/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "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/skydio/a6421d3e-fdd0-48d6-8d8f-3fd605cdf09f", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2caeb4b10d897b4a911de4dedc5d19d9", "title": "Machine Learning Engineer - Inference", "employer_name": "Together AI", "employer_slug": "together-ai", "location_text": "San Francisco", "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": 160000, "salary_max": 230000, "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": 160000, "base_salary_max": 230000, "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" ], "posted_at": "2024-06-06T19:12:19.000Z", "apply_url": "https://job-boards.greenhouse.io/togetherai/jobs/4385540007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer - Inference San Francisco About the Role Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI! Responsibilities - Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale. - Develop and optimize runtime inference services for large-scale AI applications. - Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world. - Conduct design and code reviews to ensure high standards of quality. - Create services, tools, and developer documentation to support the inference engine. - Implement robust and fault-tolerant systems for data ingestion and processing. Requirements - 3+ years of experience writing high-performance, well-tested, production-quality code. - Proficiency with Python and PyTorch. - Demonstrated experience in building high performance libraries and tooling. - Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale. - Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum - Preferred: Knowledge of AI inference", "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" }, "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": "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": 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.5d32b2d8dd2dac8392", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "2caeb4b10d897b4a911de4dedc5d19d9", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:2caeb4b10d897b4a911de4dedc5d19d9: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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "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/togetherai/jobs/4385540007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "9b805ef7461270376f7882259466247b", "title": "iOS/macOS Software Engineer", "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": "2026-03-13T23:42:03.122Z", "apply_url": "https://jobs.apple.com/en-us/details/200651661/ios-macos-software-engineer?team=SFTWR", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "iOS/macOS Software Engineer Cupertino, United States of America Are you passionate about designing and building native apps that deliver great impact and value, and eager to apply your expertise to solve real-world problems at Apple's incredible scale? Join us on the Product Integrity AI/ML team where we build the software behind Apple's hardware product development - tools used by thousands of Apple engineers and third-party manufacturers to develop, debug, and verify systems before they reach customers. We work at the intersection of hardware, software, AI/ML, and on-device intelligence, where the problems are genuinely hard and the stakes are real. Our applications are high-visibility across Apple: the decisions they enable directly influence the quality of products shipped to hundreds of millions of people. If you want to write software that matters at Apple's scale, this is the team. We are a multi-discipline software engineering team inside Hardware Engineering, delivering software that integrates cutting-edge AI/ML capabilities to support hardware and software engineering decisions. Our applications and services are used across engineering organizations, with direct influence on what ships to customers. As an iOS/macOS Software Engineer on our team, you will design, implement, and enhance the native apps that enable Apple engineers to develop, evaluate, test, and verify products before worldwide release. You'll partner with cross-functional teams across Apple, working at the boundary of software, hardware, and on-device intelligence. The work is technically demanding, and the impact is broad. Design and build production-quality Swift/SwiftUI features that leverage Apple's latest frameworks and services Solve", "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" }, "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": 4, "years_experience_max": 8, "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.query.description_excerpt.1404948166134fcb30", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "9b805ef7461270376f7882259466247b", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "iOS/macOS Software Engineer Cupertino, United States of America Are you passionate about designing and building native apps that deliver great impact and value, and eager to apply your expertise to solve real-world problems at Apple's incredible scale? Join us on the Product Integrity AI/ML team where we build the software behind Apple's hardware product development - tools used by thousands of Apple engineers and third-party manufacturers to develop, debug, and verify systems before they reach customers. We work at the intersection of hardware, software, AI/ML, and on-device intelligence, where the problems are genuinely hard and the stakes are real. Our applications are high-visibility across Apple: the decisions they enable directly influence the quality of products shipped to hundreds of millions of people. If you want to write software that matters at Apple's scale, this is the team. We are a multi-discipline software engineering team inside Hardware Engineering, delivering software that integrates cutting-edge AI/ML capabilities to support hardware and software engineering decisions. Our applications and services are used across engineering organizations, with direct influence on what ships to customers. As an iOS/macOS Software Engineer on our team, you will design, implement, and enhance the native apps that enable Apple engineers to develop, evaluate, test, and verify products before worldwide release. You'll partner with cross-functional teams across Apple, working at the boundary of software, hardware, and on-device intelligence. The work is technically demanding, and the impact is broad. Design and build production-quality Swift/SwiftUI features that leverage Apple's latest frameworks and services Solve", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:9b805ef7461270376f7882259466247b:description:intelligence", "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.8060d42d3c69fe13d4", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "9b805ef7461270376f7882259466247b", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "iOS/macOS Software Engineer Cupertino, United States of America Are you passionate about designing and building native apps that deliver great impact and value, and eager to apply your expertise to solve real-world problems at Apple's incredible scale? Join us on the Product Integrity AI/ML team where we build the software behind Apple's hardware product development - tools used by thousands of Apple engineers and third-party manufacturers to develop, debug, and verify systems before they reach customers. We work at the intersection of hardware, software, AI/ML, and on-device intelligence, where the problems are genuinely hard and the stakes are real. Our applications are high-visibility across Apple: the decisions they enable directly influence the quality of products shipped to hundreds of millions of people. If you want to write software that matters at Apple's scale, this is the team. We are a multi-discipline software engineering team inside Hardware Engineering, delivering software that integrates cutting-edge AI/ML capabilities to support hardware and software engineering decisions. Our applications and services are used across engineering organizations, with direct influence on what ships to customers. As an iOS/macOS Software Engineer on our team, you will design, implement, and enhance the native apps that enable Apple engineers to develop, evaluate, test, and verify products before worldwide release. You'll partner with cross-functional teams across Apple, working at the boundary of software, hardware, and on-device intelligence. The work is technically demanding, and the impact is broad. Design and build production-quality Swift/SwiftUI features that leverage Apple's latest frameworks and services Solve", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:9b805ef7461270376f7882259466247b:description:solve", "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.27df7f8b038ef5bfac", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "9b805ef7461270376f7882259466247b", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "iOS/macOS Software Engineer Cupertino, United States of America Are you passionate about designing and building native apps that deliver great impact and value, and eager to apply your expertise to solve real-world problems at Apple's incredible scale? Join us on the Product Integrity AI/ML team where we build the software behind Apple's hardware product development - tools used by thousands of Apple engineers and third-party manufacturers to develop, debug, and verify systems before they reach customers. We work at the intersection of hardware, software, AI/ML, and on-device intelligence, where the problems are genuinely hard and the stakes are real. Our applications are high-visibility across Apple: the decisions they enable directly influence the quality of products shipped to hundreds of millions of people. If you want to write software that matters at Apple's scale, this is the team. We are a multi-discipline software engineering team inside Hardware Engineering, delivering software that integrates cutting-edge AI/ML capabilities to support hardware and software engineering decisions. Our applications and services are used across engineering organizations, with direct influence on what ships to customers. As an iOS/macOS Software Engineer on our team, you will design, implement, and enhance the native apps that enable Apple engineers to develop, evaluate, test, and verify products before worldwide release. You'll partner with cross-functional teams across Apple, working at the boundary of software, hardware, and on-device intelligence. The work is technically demanding, and the impact is broad. Design and build production-quality Swift/SwiftUI features that leverage Apple's latest frameworks and services Solve", "matched_input": "intelligence", "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.query.description_excerpt.6c6e709d1b41623e57", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "9b805ef7461270376f7882259466247b", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "iOS/macOS Software Engineer Cupertino, United States of America Are you passionate about designing and building native apps that deliver great impact and value, and eager to apply your expertise to solve real-world problems at Apple's incredible scale? Join us on the Product Integrity AI/ML team where we build the software behind Apple's hardware product development - tools used by thousands of Apple engineers and third-party manufacturers to develop, debug, and verify systems before they reach customers. We work at the intersection of hardware, software, AI/ML, and on-device intelligence, where the problems are genuinely hard and the stakes are real. Our applications are high-visibility across Apple: the decisions they enable directly influence the quality of products shipped to hundreds of millions of people. If you want to write software that matters at Apple's scale, this is the team. We are a multi-discipline software engineering team inside Hardware Engineering, delivering software that integrates cutting-edge AI/ML capabilities to support hardware and software engineering decisions. Our applications and services are used across engineering organizations, with direct influence on what ships to customers. As an iOS/macOS Software Engineer on our team, you will design, implement, and enhance the native apps that enable Apple engineers to develop, evaluate, test, and verify products before worldwide release. You'll partner with cross-functional teams across Apple, working at the boundary of software, hardware, and on-device intelligence. The work is technically demanding, and the impact is broad. Design and build production-quality Swift/SwiftUI features that leverage Apple's latest frameworks and services Solve", "matched_input": "solve", "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.apple.com/en-us/details/200651661/ios-macos-software-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/200651661/ios-macos-software-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/200651661/ios-macos-software-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/200651661/ios-macos-software-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/200651661/ios-macos-software-engineer?team=SFTWR", "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/200651661/ios-macos-software-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": "c362efc03aff62ea72d881d6dd6069c7", "title": "Applied AI Engineer", "employer_name": "Clueso", "employer_slug": "clueso", "location_text": "Bengaluru | OnSite", "country": "IN", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "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://jobs.ashbyhq.com/clueso/8b8c98c7-4a92-4571-aa76-1edfba6cbaa8", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI Engineer Bengaluru | OnSite We're hiring an Applied AI Engineer to build the next generation of AI copilots inside Clueso. This role is about turning fast-moving LLM and vLLM capabilities into reliable, production-grade systems. You'll work on agents that understand context, reason over complex inputs, and assist users inside real workflows not demos, not prototypes. We care far more about how you think than any specific framework. If you're genuinely sharp, curious, and have spent real time working with modern AI systems, you'll do great here. WHAT YOU'LL WORK ON - Building AI copilots that operate inside real product workflows - Designing agent architectures that combine LLMs, vLLMs, and deterministic systems - Translating fuzzy user intent into structured, reliable actions - Evaluating new models as they ship-and rethinking pipelines when capabilities change - Debugging and improving AI systems based on real user behavior, not benchmarks - Working closely with product and engineering to ship AI features end-to-end This is not a research role. It's applied, hands-on, and deeply tied to shipping. WHAT WE'RE LOOKING FOR - 2+ years working with modern AI systems, LLMs, or applied machine learning. - Exceptionally strong problem-solving ability and technical judgment - Prior experience working with LLMs or vLLMs in non-trivial systems - Comfort operating in ambiguous problem spaces with incomplete information - Ability to reason about tradeoffs between AI-driven and deterministic approaches - Strong software engineering fundamentals (you write clean, debuggable code) We don't care where you learned this-startup, big tech, research", "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" }, "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" }, "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": "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": 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.5a7c2cdaa80055f212", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "c362efc03aff62ea72d881d6dd6069c7", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:c362efc03aff62ea72d881d6dd6069c7: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/clueso/8b8c98c7-4a92-4571-aa76-1edfba6cbaa8", "source_values": [ "rule:remote_status" ], "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://jobs.ashbyhq.com/clueso/8b8c98c7-4a92-4571-aa76-1edfba6cbaa8", "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/clueso/8b8c98c7-4a92-4571-aa76-1edfba6cbaa8", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6bd762860b96b1fc324e69514510ac7b", "title": "Senior AI Research Scientist", "employer_name": "Cerence Inc", "employer_slug": "cerence", "location_text": "Remote - Germany", "country": "DE", "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": 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": "2026-06-11T00:00:00.000Z", "apply_url": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Research Scientist Remote - Germany posted: Posted Yesterday", "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.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/1768267/000162828025053372/crnc-20250930.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.9d3b39a90d9ea9f99c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "6bd762860b96b1fc324e69514510ac7b", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:6bd762860b96b1fc324e69514510ac7b: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://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "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/1768267/000162828025053372/crnc-20250930.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "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://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "a57df1e6303e911329bb6d76f2f53b08", "title": "Accounting Manager", "employer_name": "FieldAI", "employer_slug": "fieldai", "location_text": "Irvine, 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": 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": 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": [ "cbinsights_unicorn" ], "posted_at": "2026-05-20T19:14:20.310Z", "apply_url": "https://jobs.lever.co/field-ai/efb2b349-f2a6-4b81-ae67-4320e78ae065", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Accounting Manager Irvine, CA FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Do Revenue Recognition & Technical Accounting - Serve as a key internal resource on ASC 606 and revenue recognition matters - Review and analyze customer contracts across software, hardware, and services arrangements - Prepare technical accounting memos 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": 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" }, "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": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "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": "professional_license", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.73a10508de623a957c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "a57df1e6303e911329bb6d76f2f53b08", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Accounting Manager Irvine, CA FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Do Revenue Recognition & Technical Accounting - Serve as a key internal resource on ASC 606 and revenue recognition matters - Review and analyze customer contracts across software, hardware, and services arrangements - Prepare technical accounting memos and", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:a57df1e6303e911329bb6d76f2f53b08:description:solve", "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.b119f8ffd8f437e602", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "a57df1e6303e911329bb6d76f2f53b08", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Accounting Manager Irvine, CA FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Do Revenue Recognition & Technical Accounting - Serve as a key internal resource on ASC 606 and revenue recognition matters - Review and analyze customer contracts across software, hardware, and services arrangements - Prepare technical accounting memos and", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:a57df1e6303e911329bb6d76f2f53b08:description:intelligence", "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.39db1f9870a1e33c3b", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "a57df1e6303e911329bb6d76f2f53b08", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Accounting Manager Irvine, CA FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Do Revenue Recognition & Technical Accounting - Serve as a key internal resource on ASC 606 and revenue recognition matters - Review and analyze customer contracts across software, hardware, and services arrangements - Prepare technical accounting memos and", "matched_input": "intelligence", "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.query.description_excerpt.a0915dd587f32aead4", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "a57df1e6303e911329bb6d76f2f53b08", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Accounting Manager Irvine, CA FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Do Revenue Recognition & Technical Accounting - Serve as a key internal resource on ASC 606 and revenue recognition matters - Review and analyze customer contracts across software, hardware, and services arrangements - Prepare technical accounting memos and", "matched_input": "solve", "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 } } ], "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.lever.co/field-ai/efb2b349-f2a6-4b81-ae67-4320e78ae065", "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://jobs.lever.co/field-ai/efb2b349-f2a6-4b81-ae67-4320e78ae065", "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/field-ai/efb2b349-f2a6-4b81-ae67-4320e78ae065", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "ad260fb96bab805249134e361336a3bf", "title": "Research Engineer - Speech & Realtime Models", "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": "2026-02-17T18:17:47.744Z", "apply_url": "https://jobs.ashbyhq.com/openai/46cd47bc-d4de-4826-aa2e-8b2e0da3c409", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Research Engineer - Speech & Realtime Models San Francisco, California, United States About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Speech & Realtime Models Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Speech & Realtime Models Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. Some of our recent work: - Introducing gpt-realtime - Demo - gpt-realtime-1.5 - ASR, TTS - May 2026 - Advancing voice intelligence with new models in the API In this role, you will: - Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a", "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" }, "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": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.40e314ff2c43e7eade", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "ad260fb96bab805249134e361336a3bf", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Research Engineer - Speech & Realtime Models San Francisco, California, United States About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Speech & Realtime Models Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Speech & Realtime Models Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. Some of our recent work: - Introducing gpt-realtime - Demo - gpt-realtime-1.5 - ASR, TTS - May 2026 - Advancing voice intelligence with new models in the API In this role, you will: - Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:ad260fb96bab805249134e361336a3bf:description:intelligence", "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.d6640d86e45ee0a460", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "ad260fb96bab805249134e361336a3bf", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Research Engineer - Speech & Realtime Models San Francisco, California, United States About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Speech & Realtime Models Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Speech & Realtime Models Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. Some of our recent work: - Introducing gpt-realtime - Demo - gpt-realtime-1.5 - ASR, TTS - May 2026 - Advancing voice intelligence with new models in the API In this role, you will: - Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:ad260fb96bab805249134e361336a3bf:description:solve", "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.03ad9840e5e7f0dff0", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "ad260fb96bab805249134e361336a3bf", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Research Engineer - Speech & Realtime Models San Francisco, California, United States About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Speech & Realtime Models Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Speech & Realtime Models Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. Some of our recent work: - Introducing gpt-realtime - Demo - gpt-realtime-1.5 - ASR, TTS - May 2026 - Advancing voice intelligence with new models in the API In this role, you will: - Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a", "matched_input": "solve", "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.query.description_excerpt.efcf2f76934adbecda", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "ad260fb96bab805249134e361336a3bf", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Research Engineer - Speech & Realtime Models San Francisco, California, United States About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Speech & Realtime Models Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Speech & Realtime Models Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. Some of our recent work: - Introducing gpt-realtime - Demo - gpt-realtime-1.5 - ASR, TTS - May 2026 - Advancing voice intelligence with new models in the API In this role, you will: - Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a", "matched_input": "intelligence", "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/46cd47bc-d4de-4826-aa2e-8b2e0da3c409", "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/46cd47bc-d4de-4826-aa2e-8b2e0da3c409", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2ea21719f9e64ed15b52b575346e4a53", "title": "AI Tutor - Korean", "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": "2026-04-01T04:38:11.000Z", "apply_url": "https://job-boards.greenhouse.io/xai/jobs/5090210007", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Tutor - Korean 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.29f922c82124647d28", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "2ea21719f9e64ed15b52b575346e4a53", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:2ea21719f9e64ed15b52b575346e4a53: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/5090210007", "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/5090210007", "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/5090210007", "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/5090210007", "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/5090210007", "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/5090210007", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "b84b2c5eca24bf4df8a586178457c904", "title": "Sr. SDE, REALM", "employer_name": "Amazon", "employer_slug": "amazon", "location_text": "Gurugram, Haryana, IND", "country": "IN", "employment_type": "internship", "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": true, "childcare_subsidy": true, "fertility_family_building_benefits": true, "adoption_assistance_offered": true, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-29T00:00:00.000Z", "apply_url": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "apply_url_verified": false, "ats": "amazon_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. SDE, REALM Gurugram, Haryana, IND Are you an experienced engineer driven to solve complex technical problems that impact hundreds of developers at scale? Do you aspire to architect and build AI-native platforms that fundamentally transform how engineering teams design, build, and deliver software - where intelligent agents handle the toil so engineers can focus on what matters? The REALM team is looking for a Senior Software Development Engineer to lead high-impact technical initiatives at the intersection of platform engineering and agentic AI. You'll build systems that remove developer friction, streamline workflows, and deliver measurable gains in productivity, efficiency, and operational excellence. Think: AI agents that automate incident investigation, LLM-powered knowledge platforms that make tribal knowledge searchable, and intelligent automation that turns days of repetitive work into minutes. If you want to build the future of how engineers work - not just write code, but fundamentally reshape the developer experience using AI - this is the role. Key job responsibilities Technical Leadership & Architecture - Design and architect scalable systems for developer productivity tools, dashboards, and automation platforms used by hundreds of engineers - Lead the technical direction for major features and products within the developer experience portfolio - Drive technical decisions and establish best practices for your team's codebase and infrastructure - Mentor SDE 1s and SDE 2s, conducting design reviews and providing technical guidance - Partner with Principal Engineers to solve complex technical challenges and align on architectural approaches Build High-Impact Products - Create automation solutions that measurably", "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.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "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": "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.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" }, "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/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "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.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "db_column": "parental_leave_weeks", "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" }, "mental_health_support": { "field": "mental_health_support", "source": "llm:greenfield:inv_371_postfix", "db_column": "mental_health_support" }, "adoption_assistance_offered": { "field": "adoption_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "adoption_assistance_offered" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" }, "fertility_family_building_benefits": { "field": "fertility_family_building_benefits", "source": "llm:greenfield:inv_371_postfix", "db_column": "fertility_family_building_benefits" } }, "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": "Industrial", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "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": 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.query.description_excerpt.31c01d1605126b7c98", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "b84b2c5eca24bf4df8a586178457c904", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. SDE, REALM Gurugram, Haryana, IND Are you an experienced engineer driven to solve complex technical problems that impact hundreds of developers at scale? Do you aspire to architect and build AI-native platforms that fundamentally transform how engineering teams design, build, and deliver software - where intelligent agents handle the toil so engineers can focus on what matters? The REALM team is looking for a Senior Software Development Engineer to lead high-impact technical initiatives at the intersection of platform engineering and agentic AI. You'll build systems that remove developer friction, streamline workflows, and deliver measurable gains in productivity, efficiency, and operational excellence. Think: AI agents that automate incident investigation, LLM-powered knowledge platforms that make tribal knowledge searchable, and intelligent automation that turns days of repetitive work into minutes. If you want to build the future of how engineers work - not just write code, but fundamentally reshape the developer experience using AI - this is the role. Key job responsibilities Technical Leadership & Architecture - Design and architect scalable systems for developer productivity tools, dashboards, and automation platforms used by hundreds of engineers - Lead the technical direction for major features and products within the developer experience portfolio - Drive technical decisions and establish best practices for your team's codebase and infrastructure - Mentor SDE 1s and SDE 2s, conducting design reviews and providing technical guidance - Partner with Principal Engineers to solve complex technical challenges and align on architectural approaches Build High-Impact Products - Create automation solutions that measurably", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:b84b2c5eca24bf4df8a586178457c904:description:solve", "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.b3a16fb7061b29c141", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "b84b2c5eca24bf4df8a586178457c904", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. SDE, REALM Gurugram, Haryana, IND Are you an experienced engineer driven to solve complex technical problems that impact hundreds of developers at scale? Do you aspire to architect and build AI-native platforms that fundamentally transform how engineering teams design, build, and deliver software - where intelligent agents handle the toil so engineers can focus on what matters? The REALM team is looking for a Senior Software Development Engineer to lead high-impact technical initiatives at the intersection of platform engineering and agentic AI. You'll build systems that remove developer friction, streamline workflows, and deliver measurable gains in productivity, efficiency, and operational excellence. Think: AI agents that automate incident investigation, LLM-powered knowledge platforms that make tribal knowledge searchable, and intelligent automation that turns days of repetitive work into minutes. If you want to build the future of how engineers work - not just write code, but fundamentally reshape the developer experience using AI - this is the role. Key job responsibilities Technical Leadership & Architecture - Design and architect scalable systems for developer productivity tools, dashboards, and automation platforms used by hundreds of engineers - Lead the technical direction for major features and products within the developer experience portfolio - Drive technical decisions and establish best practices for your team's codebase and infrastructure - Mentor SDE 1s and SDE 2s, conducting design reviews and providing technical guidance - Partner with Principal Engineers to solve complex technical challenges and align on architectural approaches Build High-Impact Products - Create automation solutions that measurably", "matched_input": "solve", "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": "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/1018724/000101872426000004/amzn-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" ], "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://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "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://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "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://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "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://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "fertility_family_building_benefits": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "mental_health_support": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "adoption_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10434782/sr-sde-realm", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" } } }, { "id": "4015e1ccfa4a9767ba348b8f2cf1df4c", "title": "AI Engineer", "employer_name": "Magna International Inc.", "employer_slug": "magna-international", "location_text": "Ramos Arizpe, MX", "country": "MX", "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://magna.wd3.myworkdayjobs.com/Magna/job/Ramos-Arizpe-MX/AI-Engineer_R00237989", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer Ramos Arizpe, MX 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": "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.2f55a5f0f512007f48", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "4015e1ccfa4a9767ba348b8f2cf1df4c", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:4015e1ccfa4a9767ba348b8f2cf1df4c: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/Ramos-Arizpe-MX/AI-Engineer_R00237989", "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/Ramos-Arizpe-MX/AI-Engineer_R00237989", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "c47366926af9135006332034956a4fc6", "title": "Sr. Applied Science , AWS Agentic AI", "employer_name": "Amazon", "employer_slug": "amazon", "location_text": "Santa Clara, California, USA", "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": 192200, "salary_max": 260000, "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": 192200, "base_salary_max": 260000, "salary_disclosed": true, "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": true, "childcare_subsidy": true, "fertility_family_building_benefits": true, "adoption_assistance_offered": true, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-22T00:00:00.000Z", "apply_url": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "apply_url_verified": false, "ats": "amazon_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Applied Science , AWS Agentic AI Santa Clara, California, USA Come join the AWS AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs", "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.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 56, "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" }, "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/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "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" }, "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": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_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" }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "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" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "db_column": "parental_leave_weeks", "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" }, "mental_health_support": { "field": "mental_health_support", "source": "llm:greenfield:inv_371_postfix", "db_column": "mental_health_support" }, "adoption_assistance_offered": { "field": "adoption_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "adoption_assistance_offered" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" }, "fertility_family_building_benefits": { "field": "fertility_family_building_benefits", "source": "llm:greenfield:inv_371_postfix", "db_column": "fertility_family_building_benefits" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 9, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Industrial", "employer_industry_source": "wikidata_sparql_industry", "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": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.32554462a35f40aa37", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "c47366926af9135006332034956a4fc6", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description matched \"solve\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Applied Science , AWS Agentic AI Santa Clara, California, USA Come join the AWS AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs", "matched_input": "solve", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:c47366926af9135006332034956a4fc6:description:solve", "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.db219a50ac99c34a7d", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "c47366926af9135006332034956a4fc6", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description matched \"intelligence\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Applied Science , AWS Agentic AI Santa Clara, California, USA Come join the AWS AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs", "matched_input": "intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:c47366926af9135006332034956a4fc6:description:intelligence", "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.3db0ee5fca2668fe65", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "c47366926af9135006332034956a4fc6", "signal_type": "query_match", "display_text": "Description: \"intelligence\"", "tooltip": "Description contains \"intelligence\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Applied Science , AWS Agentic AI Santa Clara, California, USA Come join the AWS AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs", "matched_input": "intelligence", "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.query.description_excerpt.ab540f9ebed9f5714c", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "c47366926af9135006332034956a4fc6", "signal_type": "query_match", "display_text": "Description: \"solve\"", "tooltip": "Description contains \"solve\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Applied Science , AWS Agentic AI Santa Clara, California, USA Come join the AWS AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs", "matched_input": "solve", "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": "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": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "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://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "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://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "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/1018724/000101872426000004/amzn-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" ], "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://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "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://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-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://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "fertility_family_building_benefits": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "mental_health_support": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "adoption_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10428526/sr-applied-science-aws-agentic-ai", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" } } }, { "id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "title": "AI Lab - Machine Learning Engineer", "employer_name": "Hewlett-Packard", "employer_slug": "hewlett-packard", "location_text": "Sant Cugat del Valles, Barcelona, 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", "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": "2026-06-12T10:25:24.000Z", "apply_url": "https://hp.eightfold.ai/careers/job/28359629", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Lab - Machine Learning Engineer Sant Cugat del Valles, Barcelona, Spain", "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/47217/000004721725000071/hpq-20251031.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/47217/000004721725000071/hpq-20251031.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.7db3f2babe301db62a", "query_id": "gq_1be5d9945420aa1fff16", "job_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "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": "solve intelligence", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_1be5d9945420aa1fff16:44b5e12d2e439bd9fa3a3ab4c2e89a9d: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/47217/000004721725000071/hpq-20251031.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.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://hp.eightfold.ai/careers/job/28359629", "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://hp.eightfold.ai/careers/job/28359629", "source_values": [ "rule" ], "checked_at": null } } } ], "total": 3287, "page": 16, "per_page": 24, "applied_filters": { "q": "Solve Intelligence", "quality_floor": "all" }, "hidden_unknown_benefits_count": 0, "hidden_quality_floor_count": 0, "quality_floor": "all", "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": true, "query_terms": [ "solve", "intelligence" ], "active_filter_keys": [], "visible_signal_limit": 3, "visible_trust_limit": 2 }, "event_context": { "query_context": { "query_id": "b3c0cf82-d422-4af5-a4ce-0ae017d3cda1", "issued_at": "2026-10-07T17:03:51.227Z", "route": "/jobs", "page": 16, "per_page": 24, "total_results": 3287, "sort": "relevance", "ranking_policy": "hybrid_rrf_rerank", "ranking_policy_version": "inv382.jobs.search.v2", "query_hash": "hmac_sha256:_HGFRgtn1RqtDmg8MSCu0XL51Vc8o5m92G67oNwAY3M", "filter_hash": "hmac_sha256:CXa8WcNqf8t4vwJUAguBZ01cbEAo2nphmyJ39emOY9s", "query_features": { "has_q": true, "q_term_count": 2, "q_length_bucket": "16_40", "q_pii_redacted": false, "state_count": 0, "benefit_filters": [], "quality_floor": "all" }, "exposures": [ { "result_id": "667d3c7603f1831234a2766c6e146364", "position": 361, "page_position": 1, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.004081632653061225, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 190, "quality_score": 45 } }, { "result_id": "81195ca11e9844db22b1d7b18c22f9c0", "position": 362, "page_position": 2, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3216705918312073, "rrf_score": 0.004081632653061225, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 340, "quality_score": 55 } }, { "result_id": "6ca6185906c7bfd954fb16046f103ec8", "position": 363, "page_position": 3, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.0040650406504065045, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 119, "quality_score": 55 } }, { "result_id": "1fe389a0d581b088e203c44d68ea618a", "position": 364, "page_position": 4, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3216809034347534, "rrf_score": 0.0040650406504065045, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 246, "quality_score": 55 } }, { "result_id": "4770131f4485a891b740b620e038e638", "position": 365, "page_position": 5, "retrieval_features": { "bm25_score": 0, "vector_score": 0.32168132066726685, "rrf_score": 0.004048582995951417, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 125, "quality_score": 55 } }, { "result_id": "748e4c1f937210339d133ad03c265913", "position": 366, "page_position": 6, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.004048582995951417, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 121, "quality_score": 45 } }, { "result_id": "750f04b38cdbd1265375b443615ddc6a", "position": 367, "page_position": 7, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.004032258064516129, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 131, "quality_score": 45 } }, { "result_id": "2da15a86a76fbb5ef9866580acaa5e8a", "position": 368, "page_position": 8, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3217076063156128, "rrf_score": 0.004032258064516129, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 125, "quality_score": 35 } }, { "result_id": "753112db9514c9ca09a27c440e97bebf", "position": 369, "page_position": 9, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3217649864098425, "rrf_score": 0.004016064257028112, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 134, "quality_score": 35 } }, { "result_id": "762d40d6a2b63762b5b6f6e4f7fb264b", "position": 370, "page_position": 10, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.004016064257028112, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 257, "quality_score": 45 } }, { "result_id": "7f7733c05f35b03648123d75bfa74186", "position": 371, "page_position": 11, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.004, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 231, "quality_score": 45 } }, { "result_id": "7d935599600945ad12c23778190f5d56", "position": 372, "page_position": 12, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3218424916267395, "rrf_score": 0.004, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 147, "quality_score": 35 } }, { "result_id": "8d73779c519091de59b4f1de5a99def1", "position": 373, "page_position": 13, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.00398406374501992, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 295, "quality_score": 55 } }, { "result_id": "2caeb4b10d897b4a911de4dedc5d19d9", "position": 374, "page_position": 14, "retrieval_features": { "bm25_score": 0, "vector_score": 0.32192784547805786, "rrf_score": 0.00398406374501992, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 852, "quality_score": 55 } }, { "result_id": "9b805ef7461270376f7882259466247b", "position": 375, "page_position": 15, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.003968253968253968, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 207, "quality_score": 55 } }, { "result_id": "c362efc03aff62ea72d881d6dd6069c7", "position": 376, "page_position": 16, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3219528006343352, "rrf_score": 0.003968253968253968, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 119, "quality_score": 45 } }, { "result_id": "6bd762860b96b1fc324e69514510ac7b", "position": 377, "page_position": 17, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3219562768936157, "rrf_score": 0.003952569169960474, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 118, "quality_score": 35 } }, { "result_id": "a57df1e6303e911329bb6d76f2f53b08", "position": 378, "page_position": 18, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.003952569169960474, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 139, "quality_score": 45 } }, { "result_id": "ad260fb96bab805249134e361336a3bf", "position": 379, "page_position": 19, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.003937007874015748, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 231, "quality_score": 45 } }, { "result_id": "2ea21719f9e64ed15b52b575346e4a53", "position": 380, "page_position": 20, "retrieval_features": { "bm25_score": 0, "vector_score": 0.32199573516845703, "rrf_score": 0.003937007874015748, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 189, "quality_score": 55 } }, { "result_id": "b84b2c5eca24bf4df8a586178457c904", "position": 381, "page_position": 21, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.00392156862745098, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 131, "quality_score": 45 } }, { "result_id": "4015e1ccfa4a9767ba348b8f2cf1df4c", "position": 382, "page_position": 22, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3221240255684774, "rrf_score": 0.00392156862745098, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 148, "quality_score": 35 } }, { "result_id": "c47366926af9135006332034956a4fc6", "position": 383, "page_position": 23, "retrieval_features": { "bm25_score": -6.844330787658691, "vector_score": 0, "rrf_score": 0.00390625, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 138, "quality_score": 55 } }, { "result_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "position": 384, "page_position": 24, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3223616288684815, "rrf_score": 0.00390625, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 117, "quality_score": 35 } } ] }, "context_signature": "sEXjOUVdLP_OGivqQPVbOj5uBfBA0cdICcAUiYgw408", "event_token": "sEXjOUVdLP_OGivqQPVbOj5uBfBA0cdICcAUiYgw408" } }