{ "results": [ { "id": "ad2e78962520c21cc67efa40afa6420d", "title": "Machine Learning Engineer II - Core AI/ML", "employer_name": "Remitly Global INC", "employer_slug": "remitly-global", "location_text": "Burnaby, British Columbia, Canada", "country": "CA", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "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": "2026-06-12T00:00:00.000Z", "apply_url": "https://remitly.wd5.myworkdayjobs.com/Remitly_Careers/job/Burnaby-British-Columbia-Canada/Data-Scientist-II---Core-AI-ML_R_105708", "apply_url_verified": true, "ats": "workday", "url_last_checked_alive": "2026-11-09T02:11:41.062Z", "removed_at": null, "description_excerpt": "Machine Learning Engineer II - Core AI/ML Burnaby, British Columbia, Canada Burnaby, British Columbia, Canada", "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": "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1782170/000162828026009038/rely-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/1782170/000162828026009038/rely-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": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Finance", "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": 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.49ecde1cb63f603252", "query_id": "gq_78bea5123a60839687c9", "job_id": "ad2e78962520c21cc67efa40afa6420d", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:ad2e78962520c21cc67efa40afa6420d: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 } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.trust.apply.3126232951d538903c", "query_id": "gq_78bea5123a60839687c9", "job_id": "ad2e78962520c21cc67efa40afa6420d", "signal_type": "trust_signal", "display_text": "Apply link reachable when checked", "tooltip": "The apply URL was reachable during the last recorded crawl-time liveness check; this is not a live guarantee.", "source_binding": "row_trust_evidence", "source_field": "apply_url_verified", "source_value": true, "matched_input": true, "derivation_source": "verified_source_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "trust_source_exists", "counts_for_non_trivial_query": false, "truth_verified": true, "exact": true, "priority": 10, "mobile_priority": 11, "ui": { "icon": "ExternalLink", "tone": "verified", "href": null }, "evidence_source": { "source_url": "https://remitly.wd5.myworkdayjobs.com/Remitly_Careers/job/Burnaby-British-Columbia-Canada/Data-Scientist-II---Core-AI-ML_R_105708", "source_label": "Apply link", "source_date": "2026-11-09T02:11:41.062Z" } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": "2026-11-09T02:11:41.062Z", "apply_url_verification_status": "reachable_when_last_checked", "apply_url_verification_label": "Reachable when checked at 2026-11-09T02:11:41.062Z", "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/1782170/000162828026009038/rely-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1782170/000162828026009038/rely-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://remitly.wd5.myworkdayjobs.com/Remitly_Careers/job/Burnaby-British-Columbia-Canada/Data-Scientist-II---Core-AI-ML_R_105708", "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://remitly.wd5.myworkdayjobs.com/Remitly_Careers/job/Burnaby-British-Columbia-Canada/Data-Scientist-II---Core-AI-ML_R_105708", "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://remitly.wd5.myworkdayjobs.com/Remitly_Careers/job/Burnaby-British-Columbia-Canada/Data-Scientist-II---Core-AI-ML_R_105708", "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": "13db036b11c6540352c43e9a7d59ea4e", "title": "Applied AI Scientist - Multimodal Intelligence", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Seattle, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 171600, "salary_max": 302200, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 171600, "base_salary_max": 302200, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2025-12-11T22:46:36.370Z", "apply_url": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI Scientist - Multimodal Intelligence Seattle, United States of America Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Multifaceted, amazing people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us in this truly exciting era of Artificial Intelligence to help deliver the next groundbreaking Apple products & experiences! We are continuously advancing the state of the art in Computer Vision and Machine Learning, touching all aspects of language and multimodal foundation models, from data collection, data curation to modeling, evaluation and deployment. As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming research directions in the field of multimodal foundation models that will inspire future Apple products. You will be working alongside highly accomplished and deeply technical scientists and engineers to develop pioneering solutions for challenging problems. This is a unique opportunity to be part of what forms the future of Apple products that will touch the lives of many people. We (Multimodal Intelligence Team) are looking for an Applied AI Scientist to work on the field of Generative", "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": 6, "years_experience_max": 10, "role_function": "operations", "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": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.735133bff0cf0e6633", "query_id": "gq_78bea5123a60839687c9", "job_id": "13db036b11c6540352c43e9a7d59ea4e", "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": "operations", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:13db036b11c6540352c43e9a7d59ea4e:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200636336/applied-ai-scientist-multimodal-intelligence?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "02642fe0c264957ff766f04855ebdba9", "title": "Associate Director, Product Manager - Workforce Adaptive Planning", "employer_name": "Pratt & Whitney", "employer_slug": "pratt-whitney", "location_text": "austin, Texas, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-01T00:00:00.000Z", "apply_url": "https://globalhr.wd5.myworkdayjobs.com/REC_RTX_Ext_Gateway/job/US-TX-REMOTE/Associate-Director--Product-Manager---Workforce-Adaptive-Planning_01849407/apply", "apply_url_verified": false, "ats": "phenom_people", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Associate Director, Product Manager - Workforce Adaptive Planning austin, Texas, United States of America Date Posted. 2026-06-01Country. United States of AmericaLocation. US-TX-REMOTEPosition Role Type. Unspecified. U.S. Citizen, U.S. Person, or Immigration Status Requirements. U.S. citizenship is requir...", "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": "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" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "us_citizenship_required": { "field": "us_citizenship_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "us_citizenship_required" } }, "seniority": "director_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "product", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": true, "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.26533961bae6c40ff2", "query_id": "gq_78bea5123a60839687c9", "job_id": "02642fe0c264957ff766f04855ebdba9", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Associate Director, Product Manager - Workforce Adaptive Planning austin, Texas, United States of America Date Posted. 2026-06-01Country. United States of AmericaLocation. US-TX-REMOTEPosition Role Type. Unspecified. U.S. Citizen, U.S. Person, or Immigration Status Requirements. U.S. citizenship is requir...", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:02642fe0c264957ff766f04855ebdba9:description:adaptive", "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.e60768ed5b8751b451", "query_id": "gq_78bea5123a60839687c9", "job_id": "02642fe0c264957ff766f04855ebdba9", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Associate Director, Product Manager - Workforce Adaptive Planning", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:02642fe0c264957ff766f04855ebdba9:title:adaptive", "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.07ca8d7e4605960274", "query_id": "gq_78bea5123a60839687c9", "job_id": "02642fe0c264957ff766f04855ebdba9", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Associate Director, Product Manager - Workforce Adaptive Planning", "matched_input": "adaptive", "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://globalhr.wd5.myworkdayjobs.com/REC_RTX_Ext_Gateway/job/US-TX-REMOTE/Associate-Director--Product-Manager---Workforce-Adaptive-Planning_01849407/apply", "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://globalhr.wd5.myworkdayjobs.com/REC_RTX_Ext_Gateway/job/US-TX-REMOTE/Associate-Director--Product-Manager---Workforce-Adaptive-Planning_01849407/apply", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "1de07f905040e8e3dc23899528265131", "title": "Benefits", "employer_name": "Advanced Micro Devices", "employer_slug": "advanced-micro-devices", "location_text": "Location not specified", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": 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": true, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": true, "student_loan_repayment_offered": null, "learning_budget_offered": true, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-04T16:41:40.000Z", "apply_url": "https://www.amd.com/en/corporate/careers/benefits.html", "apply_url_verified": false, "ats": "custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Benefits AMD Employee Benefits and Total Rewards Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition AMD Software: PRO", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "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" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.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" }, "learning_budget_offered": { "field": "learning_budget_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "learning_budget_offered" }, "surrogacy_assistance_offered": { "field": "surrogacy_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "surrogacy_assistance_offered" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "other", "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": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d9cfc0eed14d7e9239", "query_id": "gq_78bea5123a60839687c9", "job_id": "1de07f905040e8e3dc23899528265131", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Benefits AMD Employee Benefits and Total Rewards Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition AMD Software: PRO", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:1de07f905040e8e3dc23899528265131:description:adaptive", "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.4dae79f6c81027b7a7", "query_id": "gq_78bea5123a60839687c9", "job_id": "1de07f905040e8e3dc23899528265131", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Benefits AMD Employee Benefits and Total Rewards Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition AMD Software: PRO", "matched_input": "adaptive", "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": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.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://www.amd.com/en/corporate/careers/benefits.html", "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.amd.com/en/corporate/careers/benefits.html", "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" }, "learning_budget_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amd.com/en/corporate/careers/benefits.html", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "surrogacy_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amd.com/en/corporate/careers/benefits.html", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" } } }, { "id": "c09e87846c88d878f81ad00d132566a6", "title": "Machine Learning Engineer - 5", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "Bangalore", "country": "IN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bangalore/Machine-Learning-Engineer---5_R168703-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer - 5 Bangalore posted: Posted 30+ Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.1b41f211ad0c4036c2", "query_id": "gq_78bea5123a60839687c9", "job_id": "c09e87846c88d878f81ad00d132566a6", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:c09e87846c88d878f81ad00d132566a6:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bangalore/Machine-Learning-Engineer---5_R168703-1", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bangalore/Machine-Learning-Engineer---5_R168703-1", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bangalore/Machine-Learning-Engineer---5_R168703-1", "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://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bangalore/Machine-Learning-Engineer---5_R168703-1", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "63e0e3f88bed53886501acda46b726a4", "title": "Student Programs", "employer_name": "Advanced Micro Devices", "employer_slug": "advanced-micro-devices", "location_text": "Location not specified", "country": "unknown", "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", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-04T16:41:40.000Z", "apply_url": "https://www.amd.com/en/corporate/careers/student-programs.html", "apply_url_verified": false, "ats": "custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Student Programs AMD Student Programs | AI and Engineering Internships Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.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" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "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": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "other", "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": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.52e1d0fddd81fff6c3", "query_id": "gq_78bea5123a60839687c9", "job_id": "63e0e3f88bed53886501acda46b726a4", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Student Programs AMD Student Programs | AI and Engineering Internships Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:63e0e3f88bed53886501acda46b726a4:description:adaptive", "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.ffcdcd08d201844d2f", "query_id": "gq_78bea5123a60839687c9", "job_id": "63e0e3f88bed53886501acda46b726a4", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Student Programs AMD Student Programs | AI and Engineering Internships Skip to main content AMD Website Accessibility Statement Products Processors Accelerators Graphics Adaptive SoCs, FPGAs, & SOMs Software, Tools, & Apps Processors Server CPUs EPYC CPU Portfolio Data Center, Cloud & AI Small Business & Hosting Server CPU Specifications Business Systems Ryzen PRO Laptops Ryzen PRO Desktops Workstations PRO Technologies Ryzen AI for Business Personal & Gaming Ryzen Laptops Ryzen Desktops Advantage Gaming Laptops Advantage Gaming Desktops Ryzen Z Series Handhelds Ryzen AI for Consumer Embedded EPYC and Ryzen Partner Ecosystem Resources Product Specifications Enterprise Blogs & Insights Accelerators GPU Accelerators Instinct GPUs Documentation Cloud Graphics Adaptive Accelerators Alveo Data Center Accelerator Cards Telco Accelerator Cards DPU Accelerators Pensando Salina Ethernet Adapters Pensando Pollara 400 Alveo X3 Series Solarflare Adapters Graphics Workstations Radeon PRO Desktops AMD Advantage Premium Radeon RX Laptops AMD Advantage Premium Radeon Mobile Graphics Resources Product Specifications Documentation Adaptive SoCs, FPGAs, & SOMs Adaptive SoCs & FPGAs Versal Portfolio SoC Portfolio FPGA Portfolio Cost-Optimized Portfolio System-on-Modules (SOMs) SOM Overview Kria SOMs KD240 Drives Starter Kit KV260 Vision AI Starter Kit KR260 Robotics Starter Kit Technologies AI Engine Design Security Digital Signal Processing Functional Safety High Speed Serial Memory Solutions Power Efficiency Resources Intellectual Property Design Hubs Developer Hub Customer Training Evaluation Boards & Kits Evaluation Boards Boards & Kits Accessories Software, Tools, & Apps Processor Tools Ryzen Master Overclocking Utility PRO Technologies StoreMI Ryzen AI Software Zen Software Studio Graphics Tools & Apps AMD Software: Adrenalin Edition", "matched_input": "adaptive", "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": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/2488/000000248826000018/amd-20251227.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://www.amd.com/en/corporate/careers/student-programs.html", "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.amd.com/en/corporate/careers/student-programs.html", "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": "9d97f4832a0adc0c0ca9a8b01bd39516", "title": "Senior Applied Machine Learning Engineer", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "San Jose", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "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": "2026-05-16T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Senior-Applied-Machine-Learning-Engineer--Typographic-Intelligence_R166553", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Applied Machine Learning Engineer San Jose posted: Posted 27 Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.16881684673444fa81", "query_id": "gq_78bea5123a60839687c9", "job_id": "9d97f4832a0adc0c0ca9a8b01bd39516", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:9d97f4832a0adc0c0ca9a8b01bd39516:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Senior-Applied-Machine-Learning-Engineer--Typographic-Intelligence_R166553", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Senior-Applied-Machine-Learning-Engineer--Typographic-Intelligence_R166553", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Senior-Applied-Machine-Learning-Engineer--Typographic-Intelligence_R166553", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Senior-Applied-Machine-Learning-Engineer--Typographic-Intelligence_R166553", "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": "797845e1a940634f7e44dbccae1f2a4f", "title": "Applied Scientist, Pro Growth", "employer_name": "Thumbtack", "employer_slug": "thumbtack", "location_text": "Remote, Ontario, Toronto, Ontario, Canada, Remote, British Columbia", "country": "CA", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": 161500, "salary_max": 209000, "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": 161500, "base_salary_max": 209000, "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": [ "cbinsights_unicorn", "sequoia" ], "posted_at": "2026-05-15T19:50:52.907Z", "apply_url": "https://jobs.ashbyhq.com/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied Scientist, Pro Growth Remote, Ontario, Toronto, Ontario, Canada, Remote, British Columbia Thumbtack helps millions of people confidently care for their homes. Thumbtack is the one app you need to take care of and improve your home - from personalized guidance to AI tools and a best-in-class hiring experience. Every day in every county of the U.S., people turn to Thumbtack to complete urgent repairs, seasonal maintenance and bigger improvements. We help homeowners know which projects to do, when to do them and who to hire from our growing community of 300,000 local service businesses. If making an impact inspires you, join us. Imagine what we'll build together. About the Applied Science Team We're looking for applied scientists with deep expertise in machine learning, optimization, building data products, and/or statistical models. As part of a small product team you will have full ownership over your domain, so you should be a person who dreams big, then executes well. At Thumbtack, the Applied Science team is responsible for a wide variety of problems spanning AI, machine learning, statistics, and computer science: - Improve customer and service provider matching. Matching and optimization algorithms are fundamental to Thumbtack's product: we now service millions of matches per week. Identifying better matches between customers and service providers has an incredible impact on the experience of customers and professionals transacting on our platform. - Model complex relationships in the presence of many confounding factors. Predictive modeling problems are everywhere across our product. Our team works to", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "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" }, "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" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c38bca28dd10208294", "query_id": "gq_78bea5123a60839687c9", "job_id": "797845e1a940634f7e44dbccae1f2a4f", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:797845e1a940634f7e44dbccae1f2a4f: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/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "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://jobs.ashbyhq.com/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "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/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "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/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "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.ashbyhq.com/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "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/thumbtack/8bd503a6-e1e1-4c4a-80b4-96d1f276b6a4", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "0021fa46ab2059cc8d0cbc40593827d9", "title": "Account Executive - Enterprise", "employer_name": "Adaptive", "employer_slug": "adaptive", "location_text": "Boston, MA, United States, New York City", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "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": "2026-04-02T15:16:17.382Z", "apply_url": "https://jobs.ashbyhq.com/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Account Executive - Enterprise Boston, MA, United States, New York City What we do Adaptive is a rapidly growing vertical AI company of 50, building an AI-native ERP for real estate and construction. We have scaled to over 700 customers and have raised $26m from Emergence, a16z, and other top funds, as well as a collection of angels from companies like Brex, Ramp, Airbase, Square, and Shopify. Why join us? Power the local built environment We serve the small businesses that are building communities across our country. Your favorite local café, the new house on the corner, or the ADUs helping to solve the housing crisis were all built by our customers--those who have lived in their cities for their entire lives and have a true passion for their craft. These are creative, dynamic, skilled individuals who bring neighborhoods to life by conceiving of and constructing environments where people connect and build memories. Join a world-class team at the forefront of vertical AI We have built a culture rooted in collaboration, execution, and experience! We have deep backgrounds in finance, technology, and construction, and a fast-growing customer base. We have the momentum, team, and vision to win in this massive market. We'd love for you to join us. Role Summary We're looking for an Enterprise Account Executive to lead Adaptive's expansion into the largest construction companies in the country. Over 1000 builders rely on Adaptive to give them real-time financial clarity and help protect their profit margins through better cash", "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" }, "k401_match": { "field": "k401_match", "source": "llm:greenfield:inv_371_postfix", "db_column": "k401_match" }, "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_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" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "sales", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.e80e69a6cc79d10389", "query_id": "gq_78bea5123a60839687c9", "job_id": "0021fa46ab2059cc8d0cbc40593827d9", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Account Executive - Enterprise Boston, MA, United States, New York City What we do Adaptive is a rapidly growing vertical AI company of 50, building an AI-native ERP for real estate and construction. We have scaled to over 700 customers and have raised $26m from Emergence, a16z, and other top funds, as well as a collection of angels from companies like Brex, Ramp, Airbase, Square, and Shopify. Why join us? Power the local built environment We serve the small businesses that are building communities across our country. Your favorite local café, the new house on the corner, or the ADUs helping to solve the housing crisis were all built by our customers--those who have lived in their cities for their entire lives and have a true passion for their craft. These are creative, dynamic, skilled individuals who bring neighborhoods to life by conceiving of and constructing environments where people connect and build memories. Join a world-class team at the forefront of vertical AI We have built a culture rooted in collaboration, execution, and experience! We have deep backgrounds in finance, technology, and construction, and a fast-growing customer base. We have the momentum, team, and vision to win in this massive market. We'd love for you to join us. Role Summary We're looking for an Enterprise Account Executive to lead Adaptive's expansion into the largest construction companies in the country. Over 1000 builders rely on Adaptive to give them real-time financial clarity and help protect their profit margins through better cash", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:0021fa46ab2059cc8d0cbc40593827d9:description:adaptive", "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.236adaab0c83da4fd2", "query_id": "gq_78bea5123a60839687c9", "job_id": "0021fa46ab2059cc8d0cbc40593827d9", "signal_type": "query_match", "display_text": "Employer: \"adaptive\"", "tooltip": "Employer matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Adaptive", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:0021fa46ab2059cc8d0cbc40593827d9:employer:adaptive", "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.9e24fc5293ae72af90", "query_id": "gq_78bea5123a60839687c9", "job_id": "0021fa46ab2059cc8d0cbc40593827d9", "signal_type": "query_match", "display_text": "Employer: \"adaptive\"", "tooltip": "Employer contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Adaptive", "matched_input": "adaptive", "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": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "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/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/3369f926-e320-4a7d-8977-031cc45d4f3d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "24dbb9dce1619dd296cab9745faacd40", "title": "Machine Learning Engineer - Evergreen", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "Bucharest", "country": "RO", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bucharest/Machine-Learning-Engineer---Evergreen_R158699-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer - Evergreen Bucharest posted: Posted 30+ Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.59781b17c93f251c52", "query_id": "gq_78bea5123a60839687c9", "job_id": "24dbb9dce1619dd296cab9745faacd40", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:24dbb9dce1619dd296cab9745faacd40:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bucharest/Machine-Learning-Engineer---Evergreen_R158699-1", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bucharest/Machine-Learning-Engineer---Evergreen_R158699-1", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bucharest/Machine-Learning-Engineer---Evergreen_R158699-1", "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://adobe.wd5.myworkdayjobs.com/external_experienced/job/Bucharest/Machine-Learning-Engineer---Evergreen_R158699-1", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "a679fcf107bb9b1ff452296f6037e29f", "title": "PhD GenAI Research Scientist Intern", "employer_name": "Databricks", "employer_slug": "databricks", "location_text": "San Francisco, California", "country": "US", "employment_type": "internship", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 54, "salary_max": 60, "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": "hour", "base_salary_min": 54, "base_salary_max": 60, "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": "2023-11-07T21:36:32.000Z", "apply_url": "https://databricks.com/company/careers/open-positions/job?gh_jid=7011263002", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "PhD GenAI Research Scientist Intern San Francisco, California Company Description: At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions. The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from fine-tuning LLMs for enterprise domains, to a platform for building compound AI systems that use retrieval and agents. Mosaic AI is committed to the belief that a company's AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all. Job description: Most of the world's data+AI problems lie in enterprise domains, behind closed doors. Our research team's goal is to push the frontier of \"domain adaptation\" - how can we develop LLMs and AI systems that work well for custom domains. To do this we are tackling open research problems on a range of topics, from how to scale/automate eval, fine tune with synthetic data, retrieval augmentation, fast/efficient inference and more. You will work with our research team on projects focused on adapting LLMs and AI systems towards enterprise domains. This may include: - Adapting, improving, and evaluating a method from the literature. - Designing an entirely new method for domain adaptation. - Composing together multiple", "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" }, "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" }, "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" }, "contractor_type": { "field": "contractor_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "contractor_type" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "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": "entry", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 0, "years_experience_max": 4, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "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": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [], "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=7011263002", "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=7011263002", "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=7011263002", "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=7011263002", "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=7011263002", "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=7011263002", "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=7011263002", "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=7011263002", "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": "309a888d298a99cf5503c2cede556c67", "title": "Machine Learning Engineer, Ads Personalization", "employer_name": "Paramount Skydance Corporation", "employer_slug": "paramount-skydance", "location_text": "New York, NY", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": 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": true, "fertility_family_building_benefits": null, "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": "2026-06-12T10:25:24.000Z", "apply_url": "https://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "apply_url_verified": false, "ats": "successfactors", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer, Ads Personalization New York, NY #WeAreParamount on a mission to unleash the power of content… you in? We've got the brands, we've got the stars, we've got the power to achieve our mission to entertain the planet - now all we're missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter - both for our audiences and our employees - and aim to leave a positive mark on culture. Overview We are seeking a Machine Learning Engineer to join the PlutoTV pod. You will focus on Channel, Guide, and Schedule personalization. Your goal is to make the FAST (Free Ad-supported Streaming TV) experience feel as dynamic as a premium on-demand service. You will help build the models that select which channels appear in the guide and how content is scheduled to maximize viewer session length. This role requires deep knowledge of FAST systems and the unique constraints of linear programming. You will implement features within our GCP stack, leveraging Qdrant for content similarity and Post-training RL to optimize the \"Lean-back\" viewing experience. Why This Role Matters Modernizing Linear TV: You are part of the team transforming the static EPG (Electronic Programming Guide) into a personalized, data-driven discovery engine. Optimizing the \"Lean-Back\": Your models help users find something to watch immediately, reducing the friction inherent in \"channel surfing.\" Global", "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": "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" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/2041610/000204161026000011/psky-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/2041610/000204161026000011/psky-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "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" }, "adoption_assistance_offered": { "field": "adoption_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "adoption_assistance_offered" } }, "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": null, "employer_industry_source": null, "employer_size": null, "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.1175afbf8d37b349cb", "query_id": "gq_78bea5123a60839687c9", "job_id": "309a888d298a99cf5503c2cede556c67", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:309a888d298a99cf5503c2cede556c67: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/2041610/000204161026000011/psky-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/2041610/000204161026000011/psky-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "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://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "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://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "adoption_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.paramount.com/job/New-York-Machine-Learning-Engineer%2C-Ads-Personalization-NY-10036/1384191800/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4fdecc3070d3586bc106e8ba8182f2ab", "title": "Technical Cofounder", "employer_name": "Superset", "employer_slug": "superset", "location_text": "San Francisco, California", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "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": "2026-06-11T18:28:20.000Z", "apply_url": "https://job-boards.greenhouse.io/superset/jobs/5255447008", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Cofounder San Francisco, California Sandfox | Technical Cofounder Location: San Francisco Bay Area Format: In-office 4 days a week with flexibility for the occasional remote days The Mission Sandfox is building an adaptive buyer-led discovery platform for enterprise B2B. Our vision is a world where every business interaction adapts to buyer context, where companies understand what buyers are trying to accomplish and deliver the information, guidance, and experiences they need. Today, most B2B buying experiences are static. Websites, content hubs, and campaigns deliver the same experience regardless of who the buyer is or what they need. Sandfox transforms fragmented buyer data into structured intelligence that powers adaptive experiences, helping companies deliver relevance instead of noise. Sandfox is a portfolio company of super{set}, a venture studio that conceives, funds, and builds AI-native companies from formation through scale. We work alongside founders as operators, helping shape companies from day one. We're a small, early-stage team building something that doesn't exist yet in the market. The work is hands-on, the problems are difficult, and the opportunity to shape both product and company from the ground up is significant. Role We're looking for our first engineering hire: a Founding Engineer who will shape both the product and the technical foundation of Sandfox. You'll work directly with the founder to turn product vision into production software, establish engineering standards, and define how adaptive buyer experiences should work in practice. This role goes beyond engineering execution. We're building a new category of software where user", "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": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "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" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "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": "llm:greenfield:inv_371_postfix", "company_stage": "early", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.a22f32eab49de8c94d", "query_id": "gq_78bea5123a60839687c9", "job_id": "4fdecc3070d3586bc106e8ba8182f2ab", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Cofounder San Francisco, California Sandfox | Technical Cofounder Location: San Francisco Bay Area Format: In-office 4 days a week with flexibility for the occasional remote days The Mission Sandfox is building an adaptive buyer-led discovery platform for enterprise B2B. Our vision is a world where every business interaction adapts to buyer context, where companies understand what buyers are trying to accomplish and deliver the information, guidance, and experiences they need. Today, most B2B buying experiences are static. Websites, content hubs, and campaigns deliver the same experience regardless of who the buyer is or what they need. Sandfox transforms fragmented buyer data into structured intelligence that powers adaptive experiences, helping companies deliver relevance instead of noise. Sandfox is a portfolio company of super{set}, a venture studio that conceives, funds, and builds AI-native companies from formation through scale. We work alongside founders as operators, helping shape companies from day one. We're a small, early-stage team building something that doesn't exist yet in the market. The work is hands-on, the problems are difficult, and the opportunity to shape both product and company from the ground up is significant. Role We're looking for our first engineering hire: a Founding Engineer who will shape both the product and the technical foundation of Sandfox. You'll work directly with the founder to turn product vision into production software, establish engineering standards, and define how adaptive buyer experiences should work in practice. This role goes beyond engineering execution. We're building a new category of software where user", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:4fdecc3070d3586bc106e8ba8182f2ab:description:adaptive", "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.bedf5150c5c791a893", "query_id": "gq_78bea5123a60839687c9", "job_id": "4fdecc3070d3586bc106e8ba8182f2ab", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Technical Cofounder San Francisco, California Sandfox | Technical Cofounder Location: San Francisco Bay Area Format: In-office 4 days a week with flexibility for the occasional remote days The Mission Sandfox is building an adaptive buyer-led discovery platform for enterprise B2B. Our vision is a world where every business interaction adapts to buyer context, where companies understand what buyers are trying to accomplish and deliver the information, guidance, and experiences they need. Today, most B2B buying experiences are static. Websites, content hubs, and campaigns deliver the same experience regardless of who the buyer is or what they need. Sandfox transforms fragmented buyer data into structured intelligence that powers adaptive experiences, helping companies deliver relevance instead of noise. Sandfox is a portfolio company of super{set}, a venture studio that conceives, funds, and builds AI-native companies from formation through scale. We work alongside founders as operators, helping shape companies from day one. We're a small, early-stage team building something that doesn't exist yet in the market. The work is hands-on, the problems are difficult, and the opportunity to shape both product and company from the ground up is significant. Role We're looking for our first engineering hire: a Founding Engineer who will shape both the product and the technical foundation of Sandfox. You'll work directly with the founder to turn product vision into production software, establish engineering standards, and define how adaptive buyer experiences should work in practice. This role goes beyond engineering execution. We're building a new category of software where user", "matched_input": "adaptive", "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": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/superset/jobs/5255447008", "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://job-boards.greenhouse.io/superset/jobs/5255447008", "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/superset/jobs/5255447008", "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/superset/jobs/5255447008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "268b9aa4fd3847d80a625a714bce82b5", "title": "Applied Research Scientist, Proactive Intelligence, — Agentic Systems and Generative Modeling", "employer_name": "Apple", "employer_slug": "apple", "location_text": "Cupertino, United States of America", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 181100, "salary_max": 318400, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 181100, "base_salary_max": 318400, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-03-11T04:13:37.160Z", "apply_url": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "apply_url_verified": false, "ats": "apple_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied Research Scientist, Proactive Intelligence, — Agentic Systems and Generative Modeling Cupertino, United States of America AI represents a big opportunity to elevate Apple's products and experiences for billions of people globally. We are looking for Applied Research Scientists with a background and interest in Agentic Systems. You will be leveraging state-of-the-art Generative models to ship extraordinary products, services, and customer experiences for the iPhone, Mac, Apple Watch, iPad and more. The mission of Proactive Intelligence is to improve Apple platforms by better understanding, anticipating and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. Our team provides an opportunity to be part of an incredible research and engineering organization within Apple. The ideal candidate for this role will have industry experience working on a range of modeling problems, including Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Learning from Human Preferences and Training Large Language Models (LLMs). Working knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position. As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "doctorate", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.44fddfbeb5eb9600c5", "query_id": "gq_78bea5123a60839687c9", "job_id": "268b9aa4fd3847d80a625a714bce82b5", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:268b9aa4fd3847d80a625a714bce82b5:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.apple.com/en-us/details/200651116/applied-research-scientist-proactive-intelligence-agentic-systems-and-generative-modeling?team=MLAI", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "a9131423490a63003ddad013b763652a", "title": "Manager, FP&A - Workday Adaptive Planning", "employer_name": "Checkout.com", "employer_slug": "checkout-com", "location_text": "London, United Kingdom", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": 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": "2026-05-06T13:10:03.649Z", "apply_url": "https://jobs.ashbyhq.com/checkout.com/80e93236-ba1d-4d38-a6d6-72f250c26c29", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Manager, FP&A - Workday Adaptive Planning London, United Kingdom Company Description We're Checkout.com . You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we're behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions daily for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there's a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you've come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we're shaping the future of fintech - and we're just getting started. Checkout.com is looking for a talented and driven individual to join our Corporate FP&A team. We are a fast-scaling international organisation where Corporate FP&A sits at the centre of the broader finance team, helping to drive overall business planning and supporting the CFO and senior finance leaders on cross-functional projects. The Role Reporting directly into the Director of Corporate FP&A , this is a critical and highly visible role. You will act as the Subject Matter Expert (SME) on Workday Adaptive Planning within the Finance function.", "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" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.6c6a57b92ffe104ca7", "query_id": "gq_78bea5123a60839687c9", "job_id": "a9131423490a63003ddad013b763652a", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Manager, FP&A - Workday Adaptive Planning London, United Kingdom Company Description We're Checkout.com . You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we're behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions daily for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there's a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you've come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we're shaping the future of fintech - and we're just getting started. Checkout.com is looking for a talented and driven individual to join our Corporate FP&A team. We are a fast-scaling international organisation where Corporate FP&A sits at the centre of the broader finance team, helping to drive overall business planning and supporting the CFO and senior finance leaders on cross-functional projects. The Role Reporting directly into the Director of Corporate FP&A , this is a critical and highly visible role. You will act as the Subject Matter Expert (SME) on Workday Adaptive Planning within the Finance function.", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:a9131423490a63003ddad013b763652a:description:adaptive", "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.759ea997ce248656ed", "query_id": "gq_78bea5123a60839687c9", "job_id": "a9131423490a63003ddad013b763652a", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Manager, FP&A - Workday Adaptive Planning", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:a9131423490a63003ddad013b763652a:title:adaptive", "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.55ac87303f5419c385", "query_id": "gq_78bea5123a60839687c9", "job_id": "a9131423490a63003ddad013b763652a", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Manager, FP&A - Workday Adaptive Planning", "matched_input": "adaptive", "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/checkout.com/80e93236-ba1d-4d38-a6d6-72f250c26c29", "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/checkout.com/80e93236-ba1d-4d38-a6d6-72f250c26c29", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/checkout.com/80e93236-ba1d-4d38-a6d6-72f250c26c29", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "title": "Technical Lead, Workforce Planning (Adaptive)", "employer_name": "Take-Two Interactive", "employer_slug": "take-two-interactive", "location_text": "London, England, United Kingdom", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "GBP", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": true, "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": "2026-03-04T11:37:39.000Z", "apply_url": "https://job-boards.greenhouse.io/taketwo/jobs/7677162", "apply_url_verified": true, "ats": "greenhouse", "url_last_checked_alive": "2026-11-09T02:11:41.062Z", "removed_at": null, "description_excerpt": "Technical Lead, Workforce Planning (Adaptive) London, England, United Kingdom Who We Are Headquartered in New York City, Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for consumers around the globe. We develop and publish products principally through Rockstar Games, 2K, and Zynga. Our strategy is to create hit entertainment experiences, delivered on every platform relevant to our audience through a variety of sound business models. Our pillars - creativity, innovation, and efficiency - guide us as we strive to create the highest quality, most captivating experiences for our consumers. The Company's common stock is publicly traded on NASDAQ under the symbol TTWO. For more corporate and product information please visit our website at http://www.take2games.com . The Challenge Following our recent initiatives to modernize workforce planning, Take-Two is seeking an Adaptive Technical Lead who understands that technology is only as effective as its adoption. This is a high-impact leadership role focused on building alignment between Finance and HR data by unifying them under a single, intuitive planning ecosystem. You will serve as the functional architect of a system that replaces \"clunky\" legacy workarounds with a user-centric experience. Your mission is to satisfy Finance's need for precision while providing HR and Business teams with the \"clutter-free\" environment required to drive our strategy. This role isn't just about configuring software; it's about creating a \"Single Version of the Truth\" that empowers our global labels (2K, Rockstar, Zynga) to make data-driven talent decisions. What You'll Take On Cross-Functional", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "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/946581/000162828026037434/ttwo-20260331.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/946581/000162828026037434/ttwo-20260331.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "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": 8, "years_experience_max": 12, "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": "Media", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 45, "travel_pct": 4, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.1839e5a61174713b70", "query_id": "gq_78bea5123a60839687c9", "job_id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Lead, Workforce Planning (Adaptive) London, England, United Kingdom Who We Are Headquartered in New York City, Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for consumers around the globe. We develop and publish products principally through Rockstar Games, 2K, and Zynga. Our strategy is to create hit entertainment experiences, delivered on every platform relevant to our audience through a variety of sound business models. Our pillars - creativity, innovation, and efficiency - guide us as we strive to create the highest quality, most captivating experiences for our consumers. The Company's common stock is publicly traded on NASDAQ under the symbol TTWO. For more corporate and product information please visit our website at http://www.take2games.com . The Challenge Following our recent initiatives to modernize workforce planning, Take-Two is seeking an Adaptive Technical Lead who understands that technology is only as effective as its adoption. This is a high-impact leadership role focused on building alignment between Finance and HR data by unifying them under a single, intuitive planning ecosystem. You will serve as the functional architect of a system that replaces \"clunky\" legacy workarounds with a user-centric experience. Your mission is to satisfy Finance's need for precision while providing HR and Business teams with the \"clutter-free\" environment required to drive our strategy. This role isn't just about configuring software; it's about creating a \"Single Version of the Truth\" that empowers our global labels (2K, Rockstar, Zynga) to make data-driven talent decisions. What You'll Take On Cross-Functional", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:b3a22b4bde126a5e3cd35eeafbd2b8f1:description:adaptive", "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.ede8b06eb22e32ec8f", "query_id": "gq_78bea5123a60839687c9", "job_id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Technical Lead, Workforce Planning (Adaptive)", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:b3a22b4bde126a5e3cd35eeafbd2b8f1:title:adaptive", "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.55d3b75be19eaeeb0a", "query_id": "gq_78bea5123a60839687c9", "job_id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "signal_type": "query_match", "display_text": "Title: \"adaptive\"", "tooltip": "Title contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Technical Lead, Workforce Planning (Adaptive)", "matched_input": "adaptive", "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.trust.apply.efce1fc302af15aea5", "query_id": "gq_78bea5123a60839687c9", "job_id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "signal_type": "trust_signal", "display_text": "Apply link reachable when checked", "tooltip": "The apply URL was reachable during the last recorded crawl-time liveness check; this is not a live guarantee.", "source_binding": "row_trust_evidence", "source_field": "apply_url_verified", "source_value": true, "matched_input": true, "derivation_source": "verified_source_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "trust_source_exists", "counts_for_non_trivial_query": false, "truth_verified": true, "exact": true, "priority": 10, "mobile_priority": 11, "ui": { "icon": "ExternalLink", "tone": "verified", "href": null }, "evidence_source": { "source_url": "https://job-boards.greenhouse.io/taketwo/jobs/7677162", "source_label": "Apply link", "source_date": "2026-11-09T02:11:41.062Z" } } ], "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": "2026-11-09T02:11:41.062Z", "apply_url_verification_status": "reachable_when_last_checked", "apply_url_verification_label": "Reachable when checked at 2026-11-09T02:11:41.062Z", "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/946581/000162828026037434/ttwo-20260331.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/946581/000162828026037434/ttwo-20260331.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://job-boards.greenhouse.io/taketwo/jobs/7677162", "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/taketwo/jobs/7677162", "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/taketwo/jobs/7677162", "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" }, "fertility_family_building_benefits": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/taketwo/jobs/7677162", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" } } }, { "id": "598edf2da4643d6ed7b25106604e1069", "title": "Software Engineer, Backend", "employer_name": "Adaptyv", "employer_slug": "adaptyv", "location_text": "Lausanne / Hybrid / Remote | Hybrid | Remote", "country": "CH", "employment_type": "unknown", "remote_status": "hybrid", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 2, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/adaptyv/d3475c06-3180-4d89-8ecf-8b889cff92bb", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Backend Lausanne / Hybrid / Remote | Hybrid | Remote Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You'll build backend systems that make our lab programmable. You'll architect data pipelines that process large-scale protein characterization data, build APIs that integrate laboratory instruments and robotics into our software stack, and work closely with scientists and automation engineers to translate complex molecular biology workflows into reliable, scalable software. This is not SaaS slop, you're", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": 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" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "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": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.155888cd4c4119ed39", "query_id": "gq_78bea5123a60839687c9", "job_id": "598edf2da4643d6ed7b25106604e1069", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:598edf2da4643d6ed7b25106604e1069: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/adaptyv/d3475c06-3180-4d89-8ecf-8b889cff92bb", "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/adaptyv/d3475c06-3180-4d89-8ecf-8b889cff92bb", "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/adaptyv/d3475c06-3180-4d89-8ecf-8b889cff92bb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptyv/d3475c06-3180-4d89-8ecf-8b889cff92bb", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2e7966358d4ad4174369583a8f1bcf75", "title": "Community Manager", "employer_name": "Adaptyv", "employer_slug": "adaptyv", "location_text": "Lausanne / Hybrid / Remote | Hybrid | Remote", "country": "CH", "employment_type": "unknown", "remote_status": "hybrid", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 2, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/adaptyv/5a44f0eb-8d0d-4b04-9d51-9933f899aeaf", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Community Manager Lausanne / Hybrid / Remote | Hybrid | Remote Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You'll be the person who makes sure Adaptyv shows up well in public, every day. That means managing our social presence across X and LinkedIn, running the Proteinbase https://proteinbase.com community, owning the participant side of our open competitions and hackathons, and triaging inbound community and customer messages. Whatever it takes to keep our community-facing surface area", "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" }, "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": 5, "years_experience_max": 9, "role_function": "marketing", "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.b4a39b9213915b2a6e", "query_id": "gq_78bea5123a60839687c9", "job_id": "2e7966358d4ad4174369583a8f1bcf75", "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": "marketing", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:2e7966358d4ad4174369583a8f1bcf75: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/adaptyv/5a44f0eb-8d0d-4b04-9d51-9933f899aeaf", "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/adaptyv/5a44f0eb-8d0d-4b04-9d51-9933f899aeaf", "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/adaptyv/5a44f0eb-8d0d-4b04-9d51-9933f899aeaf", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "d0309566ec55ebbf17e4f258e052e0a6", "title": "Account Executive - Mid Market", "employer_name": "Adaptive", "employer_slug": "adaptive", "location_text": "Boston, MA, United States, New York City", "country": "US", "employment_type": "contract", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "a16z" ], "posted_at": "2025-04-25T18:58:04.905Z", "apply_url": "https://jobs.ashbyhq.com/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Account Executive - Mid Market Boston, MA, United States, New York City What we do Adaptive is a rapidly growing vertical AI company of 50, building an AI-native ERP for real estate and construction. We have scaled to over 700 customers and have raised $26m from Emergence, a16z, and other top funds, as well as a collection of angels from companies like Brex, Ramp, Airbase, Square, and Shopify. Why join us? Power the local built environment We serve the small businesses that are building communities across our country. Your favorite local café, the new house on the corner, or the ADUs helping to solve the housing crisis were all built by our customers--those who have lived in their cities for their entire lives and have a true passion for their craft. These are creative, dynamic, skilled individuals who bring neighborhoods to life by conceiving of and constructing environments where people connect and build memories. Join a world-class team at the forefront of vertical AI We have built a culture rooted in collaboration, execution, and experience! We have deep backgrounds in finance, technology, and construction, and a fast-growing customer base. We have the momentum, team, and vision to win in this massive market. We'd love for you to join us. Role Summary We're looking for a Mid-Market Account Executive to help us bring Adaptive to more builders across the country. Over 1000 builders rely on Adaptive to give them real-time financial clarity and help protect their profit margins through better cash", "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" }, "k401_match": { "field": "k401_match", "source": "llm:greenfield:inv_371_postfix", "db_column": "k401_match" }, "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_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" }, "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": "sales", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.5095ec730a5123b9d7", "query_id": "gq_78bea5123a60839687c9", "job_id": "d0309566ec55ebbf17e4f258e052e0a6", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Account Executive - Mid Market Boston, MA, United States, New York City What we do Adaptive is a rapidly growing vertical AI company of 50, building an AI-native ERP for real estate and construction. We have scaled to over 700 customers and have raised $26m from Emergence, a16z, and other top funds, as well as a collection of angels from companies like Brex, Ramp, Airbase, Square, and Shopify. Why join us? Power the local built environment We serve the small businesses that are building communities across our country. Your favorite local café, the new house on the corner, or the ADUs helping to solve the housing crisis were all built by our customers--those who have lived in their cities for their entire lives and have a true passion for their craft. These are creative, dynamic, skilled individuals who bring neighborhoods to life by conceiving of and constructing environments where people connect and build memories. Join a world-class team at the forefront of vertical AI We have built a culture rooted in collaboration, execution, and experience! We have deep backgrounds in finance, technology, and construction, and a fast-growing customer base. We have the momentum, team, and vision to win in this massive market. We'd love for you to join us. Role Summary We're looking for a Mid-Market Account Executive to help us bring Adaptive to more builders across the country. Over 1000 builders rely on Adaptive to give them real-time financial clarity and help protect their profit margins through better cash", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:d0309566ec55ebbf17e4f258e052e0a6:description:adaptive", "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.223c83cf473a1db687", "query_id": "gq_78bea5123a60839687c9", "job_id": "d0309566ec55ebbf17e4f258e052e0a6", "signal_type": "query_match", "display_text": "Employer: \"adaptive\"", "tooltip": "Employer matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Adaptive", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:d0309566ec55ebbf17e4f258e052e0a6:employer:adaptive", "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.72df777632d1ae4933", "query_id": "gq_78bea5123a60839687c9", "job_id": "d0309566ec55ebbf17e4f258e052e0a6", "signal_type": "query_match", "display_text": "Employer: \"adaptive\"", "tooltip": "Employer contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Adaptive", "matched_input": "adaptive", "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": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "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/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptive/9d83a314-acca-43ad-bd73-297e24bfc523", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "bf239575f63b2a9713fcc58ef4139a4b", "title": "Data Scientist, Lab & Protein Data", "employer_name": "Adaptyv", "employer_slug": "adaptyv", "location_text": "Lausanne | OnSite", "country": "CH", "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": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/adaptyv/d15ab16a-2a89-43e5-b8c1-46e1badef5f2", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Scientist, Lab & Protein Data Lausanne | OnSite Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You'll build out the data science layer of Adaptyv's foundry - the work that turns tens of thousands of raw, messy experimental readouts into clean, trustworthy, structured data that our customers, our models, and our own scientists can rely on. Binding (BLI/SPR), developability, biophysical, and functional assays all produce data at scale; your job is to make that", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": 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" }, "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": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 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.5fa3fe4399a6bbd7ce", "query_id": "gq_78bea5123a60839687c9", "job_id": "bf239575f63b2a9713fcc58ef4139a4b", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:bf239575f63b2a9713fcc58ef4139a4b: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/adaptyv/d15ab16a-2a89-43e5-b8c1-46e1badef5f2", "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/adaptyv/d15ab16a-2a89-43e5-b8c1-46e1badef5f2", "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/adaptyv/d15ab16a-2a89-43e5-b8c1-46e1badef5f2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "fcdbf64a564d22aae659948e172d3ff9", "title": "Workday Finance Systems Manager", "employer_name": "Genius Sports Ltd", "employer_slug": "genius-sports", "location_text": "London, England, United Kingdom", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": 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": "2025-10-24T14:13:54.000Z", "apply_url": "https://boards.greenhouse.io/geniussports/jobs/7507439003?gh_jid=7507439003", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Workday Finance Systems Manager London, England, United Kingdom By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalised than ever before. Learn more at geniussports.com THE ROLE: The Finance Systems Manager manages a small team responsible for the day to day running of Workday Financials and Adaptive Planning. The role reports to the Group Finance Director within the Global Finance team. The role is responsible for the administration, maintenance and optimization of the Workday Financials and Adaptive Planning systems. The role works closely with IT to ensure the system meets business requirements and operates smoothly. Duties & Responsibilities - Manage and maintain Workday Financials and Adaptive Planning in a well-controlled and documented system environment - Lead the Finance Systems team, motivating team members and encouraging them to learn and develop through their work - Provide technical assistance for core financial processes - Build and maintain excellent working relationships with key members of the Finance team and other global stakeholders - Hold regular meetings with key stakeholders - Stay on top of Workday updates - Advise on system enhancements when appropriate for both Finance and the Business - Run pilots for new functionality/system changes utilizing Finance team members for key roles in the pilots - Optimise processes to achieve measurable outcomes - Roll out ways of working which facilitate user self service - Ensure system changes are communicated to", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 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": "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" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "finance", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3e7cfa75c4421a509a", "query_id": "gq_78bea5123a60839687c9", "job_id": "fcdbf64a564d22aae659948e172d3ff9", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Workday Finance Systems Manager London, England, United Kingdom By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalised than ever before. Learn more at geniussports.com THE ROLE: The Finance Systems Manager manages a small team responsible for the day to day running of Workday Financials and Adaptive Planning. The role reports to the Group Finance Director within the Global Finance team. The role is responsible for the administration, maintenance and optimization of the Workday Financials and Adaptive Planning systems. The role works closely with IT to ensure the system meets business requirements and operates smoothly. Duties & Responsibilities - Manage and maintain Workday Financials and Adaptive Planning in a well-controlled and documented system environment - Lead the Finance Systems team, motivating team members and encouraging them to learn and develop through their work - Provide technical assistance for core financial processes - Build and maintain excellent working relationships with key members of the Finance team and other global stakeholders - Hold regular meetings with key stakeholders - Stay on top of Workday updates - Advise on system enhancements when appropriate for both Finance and the Business - Run pilots for new functionality/system changes utilizing Finance team members for key roles in the pilots - Optimise processes to achieve measurable outcomes - Roll out ways of working which facilitate user self service - Ensure system changes are communicated to", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:fcdbf64a564d22aae659948e172d3ff9:description:adaptive", "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.db40b47e82b766b659", "query_id": "gq_78bea5123a60839687c9", "job_id": "fcdbf64a564d22aae659948e172d3ff9", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Workday Finance Systems Manager London, England, United Kingdom By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalised than ever before. Learn more at geniussports.com THE ROLE: The Finance Systems Manager manages a small team responsible for the day to day running of Workday Financials and Adaptive Planning. The role reports to the Group Finance Director within the Global Finance team. The role is responsible for the administration, maintenance and optimization of the Workday Financials and Adaptive Planning systems. The role works closely with IT to ensure the system meets business requirements and operates smoothly. Duties & Responsibilities - Manage and maintain Workday Financials and Adaptive Planning in a well-controlled and documented system environment - Lead the Finance Systems team, motivating team members and encouraging them to learn and develop through their work - Provide technical assistance for core financial processes - Build and maintain excellent working relationships with key members of the Finance team and other global stakeholders - Hold regular meetings with key stakeholders - Stay on top of Workday updates - Advise on system enhancements when appropriate for both Finance and the Business - Run pilots for new functionality/system changes utilizing Finance team members for key roles in the pilots - Optimise processes to achieve measurable outcomes - Roll out ways of working which facilitate user self service - Ensure system changes are communicated to", "matched_input": "adaptive", "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://boards.greenhouse.io/geniussports/jobs/7507439003?gh_jid=7507439003", "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://boards.greenhouse.io/geniussports/jobs/7507439003?gh_jid=7507439003", "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://boards.greenhouse.io/geniussports/jobs/7507439003?gh_jid=7507439003", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "439ada73e63e32af580a2a289daff8f0", "title": "Dental Hygienist - Advanced Clinical", "employer_name": "Department of Veterans Affairs", "employer_slug": "department-of-veterans-affairs", "location_text": "Sheridan, Wyoming", "country": "US", "employment_type": "part_time", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 67970, "salary_max": 88356, "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": 67970, "base_salary_max": 88356, "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": [], "posted_at": "2026-04-29T15:18:20.000Z", "apply_url": "https://www.usajobs.gov:443/job/867259700", "apply_url_verified": false, "ats": "usajobs", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Dental Hygienist - Advanced Clinical Sheridan, Wyoming Summary Dental hygienists at this level are advanced-level practitioners in assigned areas. Higher-level duties consist of significant scope, complexity, and range of variety, and will be performed most of the hygienist's time. Serves as coordinator of the Dental Hygiene Student Program and provides hands-on clinical instruction to dental hygiene or dental assisting students during their clinic rotations, including all training required by the Sheridan College Dental Hygiene Program. Duties Performs comprehensive medical assessments and appropriate adaptation techniques to provide safe and effective periodontal care in severely compromised patients. Dental screenings independently outside of the dental clinic at inpatient residential areas and adapt treatment based on findings of medically/mentally/physically compromised patients. Uses more advanced adjunctive, diagnostic tools and techniques for monitoring clinical disease processes. Designs customized adaptive aids based on assessment of patients' abilities and disabilities. Manages advanced medical and behavioral risk factors for medically/mentally/physically compromised patients including indication of administration of adjunctive therapies Serves as member of relevant hospital committees and patient wellness programs. Provides oral/written tobacco cessation education and works with our tobacco cessation coordinator. Provides oral/written training protocols for the dental hygiene students. Provides oral health presentations to nursing staff, diabetic educators, and other disciplines. Sets up operatory for planned dental procedure and cleans dental unit for timely turnover. Handles instruments safely, accurately, and efficiently. Assesses clinical findings, including normal and critical lab results, and adapt care based on findings. Interviews patient and assesses patient's medical, dental, anxiety/phobias, medications and comorbidities.", "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": false, "benefit_last_verified": null, "hire_states_allowed": [ "WY" ], "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": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "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" }, "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" }, "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" }, "hire_states_allowed": { "field": "hire_states_allowed", "source": "rule:state_eligibility", "db_column": "hire_states_allowed" }, "us_citizenship_required": { "field": "us_citizenship_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "us_citizenship_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "healthcare", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Healthcare", "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": true, "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.6b1bfb8fda58ebe97a", "query_id": "gq_78bea5123a60839687c9", "job_id": "439ada73e63e32af580a2a289daff8f0", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description matched \"adaptive\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Dental Hygienist - Advanced Clinical Sheridan, Wyoming Summary Dental hygienists at this level are advanced-level practitioners in assigned areas. Higher-level duties consist of significant scope, complexity, and range of variety, and will be performed most of the hygienist's time. Serves as coordinator of the Dental Hygiene Student Program and provides hands-on clinical instruction to dental hygiene or dental assisting students during their clinic rotations, including all training required by the Sheridan College Dental Hygiene Program. Duties Performs comprehensive medical assessments and appropriate adaptation techniques to provide safe and effective periodontal care in severely compromised patients. Dental screenings independently outside of the dental clinic at inpatient residential areas and adapt treatment based on findings of medically/mentally/physically compromised patients. Uses more advanced adjunctive, diagnostic tools and techniques for monitoring clinical disease processes. Designs customized adaptive aids based on assessment of patients' abilities and disabilities. Manages advanced medical and behavioral risk factors for medically/mentally/physically compromised patients including indication of administration of adjunctive therapies Serves as member of relevant hospital committees and patient wellness programs. Provides oral/written tobacco cessation education and works with our tobacco cessation coordinator. Provides oral/written training protocols for the dental hygiene students. Provides oral health presentations to nursing staff, diabetic educators, and other disciplines. Sets up operatory for planned dental procedure and cleans dental unit for timely turnover. Handles instruments safely, accurately, and efficiently. Assesses clinical findings, including normal and critical lab results, and adapt care based on findings. Interviews patient and assesses patient's medical, dental, anxiety/phobias, medications and comorbidities.", "matched_input": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:439ada73e63e32af580a2a289daff8f0:description:adaptive", "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.1f7e5d755636e65e7f", "query_id": "gq_78bea5123a60839687c9", "job_id": "439ada73e63e32af580a2a289daff8f0", "signal_type": "query_match", "display_text": "Description: \"adaptive\"", "tooltip": "Description contains \"adaptive\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Dental Hygienist - Advanced Clinical Sheridan, Wyoming Summary Dental hygienists at this level are advanced-level practitioners in assigned areas. Higher-level duties consist of significant scope, complexity, and range of variety, and will be performed most of the hygienist's time. Serves as coordinator of the Dental Hygiene Student Program and provides hands-on clinical instruction to dental hygiene or dental assisting students during their clinic rotations, including all training required by the Sheridan College Dental Hygiene Program. Duties Performs comprehensive medical assessments and appropriate adaptation techniques to provide safe and effective periodontal care in severely compromised patients. Dental screenings independently outside of the dental clinic at inpatient residential areas and adapt treatment based on findings of medically/mentally/physically compromised patients. Uses more advanced adjunctive, diagnostic tools and techniques for monitoring clinical disease processes. Designs customized adaptive aids based on assessment of patients' abilities and disabilities. Manages advanced medical and behavioral risk factors for medically/mentally/physically compromised patients including indication of administration of adjunctive therapies Serves as member of relevant hospital committees and patient wellness programs. Provides oral/written tobacco cessation education and works with our tobacco cessation coordinator. Provides oral/written training protocols for the dental hygiene students. Provides oral health presentations to nursing staff, diabetic educators, and other disciplines. Sets up operatory for planned dental procedure and cleans dental unit for timely turnover. Handles instruments safely, accurately, and efficiently. Assesses clinical findings, including normal and critical lab results, and adapt care based on findings. Interviews patient and assesses patient's medical, dental, anxiety/phobias, medications and comorbidities.", "matched_input": "adaptive", "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://www.usajobs.gov:443/job/867259700", "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.usajobs.gov:443/job/867259700", "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.usajobs.gov:443/job/867259700", "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" }, "hire_states_allowed": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.usajobs.gov:443/job/867259700", "source_values": [ "rule:state_eligibility" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.usajobs.gov:443/job/867259700", "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.usajobs.gov:443/job/867259700", "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": "1bf38f1a3b943a5e09e638cd920c78f7", "title": "Software Engineer, Product", "employer_name": "Adaptyv", "employer_slug": "adaptyv", "location_text": "Lausanne / Hybrid / Remote | Hybrid | Remote", "country": "CH", "employment_type": "unknown", "remote_status": "hybrid", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 2, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/adaptyv/34e28741-b3fc-4536-b666-1e690c8f33f5", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer, Product Lausanne / Hybrid / Remote | Hybrid | Remote Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You'll work across LabOS - our internal software platform - building the orchestration layer that coordinates everything from experiment scheduling to execution to data capture and results processing. This is full-stack product engineering at the intersection of software and physical-world biology. Day-to-day, that can mean things like: - Creating interfaces and APIs that give scientists", "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" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "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": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.eee10a5bc409527a02", "query_id": "gq_78bea5123a60839687c9", "job_id": "1bf38f1a3b943a5e09e638cd920c78f7", "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": "adaptive", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_78bea5123a60839687c9:1bf38f1a3b943a5e09e638cd920c78f7: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/adaptyv/34e28741-b3fc-4536-b666-1e690c8f33f5", "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/adaptyv/34e28741-b3fc-4536-b666-1e690c8f33f5", "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/adaptyv/34e28741-b3fc-4536-b666-1e690c8f33f5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/adaptyv/34e28741-b3fc-4536-b666-1e690c8f33f5", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "a09fa2ebcadf9afbabfb4c99a7c1fc35", "title": "SW Development Engineer, AWS Elastic Network Adapter Firmware team", "employer_name": "Amazon", "employer_slug": "amazon", "location_text": "Haifa, Haifa, ISR", "country": "IL", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "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": "2026-02-03T00:00:00.000Z", "apply_url": "https://www.amazon.jobs/en/jobs/3172552/sw-development-engineer-aws-elastic-network-adapter-firmware-team", "apply_url_verified": false, "ats": "amazon_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "SW Development Engineer, AWS Elastic Network Adapter Firmware team Haifa, Haifa, ISR Annapurna Labs, as part of Amazon Web Services (AWS), develops innovative hardware and software for AWS cloud customers. Annapurna Labs is like a big start-up in AWS. We develop cutting-edge technologies, work with amazingly talented engineers, and truly shape the future. Thanks to our teams' breadth of professional engineers, we have been able to improve AWS cloud networking infrastructure, with products such as Elastic Network Adapter (ENA), Elastic Fabric Adapter (EFA), and Scalable Reliable Datagram (SRD). Our products are at the heart of the cloud, playing a key role, and used by millions and millions of customers! Working for Annapurna Labs is thrilling, fast-paced, and a constant learning experience. As an ENA Firmware SW development engineer, you will be responsible for developing features for Annapurna Labs next-generation hardware, to enable high network bandwidth and packets-per-seconds (PPS) performance, with consistently low latency. You will work to bring up a broad selection of instance types, optimized for various use cases, to suit each of our customer's needs, such as varying combinations of CPU, memory, storage, and networking capabilities. As an ENA Firmware SW development engineer, you will play a key role in shaping architecture definitions and SW system designs, and help to resolve complex customer issues. You will continuously evolve technically, while working to monitor AWS cloud health, maintain high quality standards, develop highly-optimized code, and provide exceptional customer satisfaction. Basic Qualifications: - Bachelor's degree in computer science or electrical", "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": 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/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" }, "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/1018724/000101872426000004/amzn-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.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" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" } }, "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": "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": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [], "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": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/3172552/sw-development-engineer-aws-elastic-network-adapter-firmware-team", "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/3172552/sw-development-engineer-aws-elastic-network-adapter-firmware-team", "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" }, "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/3172552/sw-development-engineer-aws-elastic-network-adapter-firmware-team", "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.amazon.jobs/en/jobs/3172552/sw-development-engineer-aws-elastic-network-adapter-firmware-team", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": null } } } ], "total": 5250, "page": 5, "per_page": 24, "applied_filters": { "q": "Adaptive", "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": false, "query_terms": [ "adaptive" ], "active_filter_keys": [], "visible_signal_limit": 3, "visible_trust_limit": 2 }, "event_context": { "query_context": { "query_id": "46d4c116-f256-4bdd-9897-674fa6a8d300", "issued_at": "2026-11-15T22:29:56.647Z", "route": "/jobs", "page": 5, "per_page": 24, "total_results": 5250, "sort": "relevance", "ranking_policy": "hybrid_rrf_rerank", "ranking_policy_version": "inv382.jobs.search.v2", "query_hash": "hmac_sha256:YRdFJBK2MCA5Q-Ni11CQo-PnYD2F10R16IuUSRjMgXc", "filter_hash": "hmac_sha256:CXa8WcNqf8t4vwJUAguBZ01cbEAo2nphmyJ39emOY9s", "query_features": { "has_q": true, "q_term_count": 1, "q_length_bucket": "1_15", "q_pii_redacted": false, "state_count": 0, "benefit_filters": [], "quality_floor": "all" }, "exposures": [ { "result_id": "ad2e78962520c21cc67efa40afa6420d", "position": 97, "page_position": 1, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3910594401079247, "rrf_score": 0.008547008547008548, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "13db036b11c6540352c43e9a7d59ea4e", "position": 98, "page_position": 2, "retrieval_features": { "bm25_score": 0, "vector_score": 0.39209790849393633, "rrf_score": 0.00847457627118644, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 338, "quality_score": 55 } }, { "result_id": "02642fe0c264957ff766f04855ebdba9", "position": 99, "page_position": 3, "retrieval_features": { "bm25_score": -6.926811695098877, "vector_score": 0, "rrf_score": 0.00847457627118644, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 167, "quality_score": 45 } }, { "result_id": "1de07f905040e8e3dc23899528265131", "position": 100, "page_position": 4, "retrieval_features": { "bm25_score": -6.910952091217041, "vector_score": 0, "rrf_score": 0.008403361344537815, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 164, "quality_score": 45 } }, { "result_id": "c09e87846c88d878f81ad00d132566a6", "position": 101, "page_position": 5, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3922603545266493, "rrf_score": 0.008403361344537815, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 187, "quality_score": 35 } }, { "result_id": "63e0e3f88bed53886501acda46b726a4", "position": 102, "page_position": 6, "retrieval_features": { "bm25_score": -6.910952091217041, "vector_score": 0, "rrf_score": 0.008333333333333333, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 164, "quality_score": 45 } }, { "result_id": "9d97f4832a0adc0c0ca9a8b01bd39516", "position": 103, "page_position": 7, "retrieval_features": { "bm25_score": 0, "vector_score": 0.392406266701408, "rrf_score": 0.008333333333333333, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 183, "quality_score": 35 } }, { "result_id": "797845e1a940634f7e44dbccae1f2a4f", "position": 104, "page_position": 8, "retrieval_features": { "bm25_score": 0, "vector_score": 0.39242478035614303, "rrf_score": 0.008264462809917356, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 184, "quality_score": 55 } }, { "result_id": "0021fa46ab2059cc8d0cbc40593827d9", "position": 105, "page_position": 9, "retrieval_features": { "bm25_score": -6.813244819641113, "vector_score": 0, "rrf_score": 0.008264462809917356, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 227, "quality_score": 45 } }, { "result_id": "24dbb9dce1619dd296cab9745faacd40", "position": 106, "page_position": 10, "retrieval_features": { "bm25_score": 0, "vector_score": 0.39260747388645856, "rrf_score": 0.00819672131147541, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 187, "quality_score": 35 } }, { "result_id": "a679fcf107bb9b1ff452296f6037e29f", "position": 107, "page_position": 11, "retrieval_features": { "bm25_score": -6.813244819641113, "vector_score": 0, "rrf_score": 0.00819672131147541, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 1104, "quality_score": 55 } }, { "result_id": "309a888d298a99cf5503c2cede556c67", "position": 108, "page_position": 12, "retrieval_features": { "bm25_score": 0, "vector_score": 0.39281432011170125, "rrf_score": 0.008130081300813009, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "4fdecc3070d3586bc106e8ba8182f2ab", "position": 109, "page_position": 13, "retrieval_features": { "bm25_score": -6.6566548347473145, "vector_score": 0, "rrf_score": 0.008130081300813009, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 157, "quality_score": 45 } }, { "result_id": "268b9aa4fd3847d80a625a714bce82b5", "position": 110, "page_position": 14, "retrieval_features": { "bm25_score": 0, "vector_score": 0.392848069115149, "rrf_score": 0.008064516129032258, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 249, "quality_score": 55 } }, { "result_id": "a9131423490a63003ddad013b763652a", "position": 111, "page_position": 15, "retrieval_features": { "bm25_score": -6.6566548347473145, "vector_score": 0, "rrf_score": 0.008064516129032258, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 193, "quality_score": 45 } }, { "result_id": "b3a22b4bde126a5e3cd35eeafbd2b8f1", "position": 112, "page_position": 16, "retrieval_features": { "bm25_score": -6.6566548347473145, "vector_score": 0, "rrf_score": 0.008, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 256, "quality_score": 45 } }, { "result_id": "598edf2da4643d6ed7b25106604e1069", "position": 113, "page_position": 17, "retrieval_features": { "bm25_score": 0, "vector_score": 0.38042215646571365, "rrf_score": 0.008, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 158, "quality_score": 45 } }, { "result_id": "2e7966358d4ad4174369583a8f1bcf75", "position": 114, "page_position": 18, "retrieval_features": { "bm25_score": 0, "vector_score": 0.382372576523642, "rrf_score": 0.007936507936507936, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 158, "quality_score": 45 } }, { "result_id": "d0309566ec55ebbf17e4f258e052e0a6", "position": 115, "page_position": 19, "retrieval_features": { "bm25_score": -6.6566548347473145, "vector_score": 0, "rrf_score": 0.007936507936507936, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 569, "quality_score": 45 } }, { "result_id": "bf239575f63b2a9713fcc58ef4139a4b", "position": 116, "page_position": 20, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3845936289187448, "rrf_score": 0.007874015748031496, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 158, "quality_score": 45 } }, { "result_id": "fcdbf64a564d22aae659948e172d3ff9", "position": 117, "page_position": 21, "retrieval_features": { "bm25_score": -6.6566548347473145, "vector_score": 0, "rrf_score": 0.007874015748031496, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 387, "quality_score": 45 } }, { "result_id": "439ada73e63e32af580a2a289daff8f0", "position": 118, "page_position": 22, "retrieval_features": { "bm25_score": -6.507101535797119, "vector_score": 0, "rrf_score": 0.0078125, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 200, "quality_score": 55 } }, { "result_id": "1bf38f1a3b943a5e09e638cd920c78f7", "position": 119, "page_position": 23, "retrieval_features": { "bm25_score": 0, "vector_score": 0.38563076810928465, "rrf_score": 0.0078125, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 158, "quality_score": 45 } }, { "result_id": "a09fa2ebcadf9afbabfb4c99a7c1fc35", "position": 120, "page_position": 24, "retrieval_features": { "bm25_score": -6.507101535797119, "vector_score": 0, "rrf_score": 0.007751937984496124, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 285, "quality_score": 45 } } ] }, "context_signature": "jAugvPy0nkku4KffUCXSSr1oz6pl3tYP39qgWmhSyo0", "event_token": "jAugvPy0nkku4KffUCXSSr1oz6pl3tYP39qgWmhSyo0" } }