{
  "results": [
    {
      "id": "49e58ae39ff5da27235f92c94434bce6",
      "title": "Head of Engineering (Data & SWE)",
      "employer_name": "Hilbert",
      "employer_slug": "hilbert",
      "location_text": "San Francisco, California, United States",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "options"
      ],
      "k401_match": 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": [
        "a16z"
      ],
      "posted_at": "2026-02-26T01:02:56.016Z",
      "apply_url": "https://jobs.ashbyhq.com/hilberts/9356cb85-e325-445e-b4d6-1c80114ec8f0",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Head of Engineering (Data & SWE) San Francisco, California, United States The Mission: Build the Machine that Builds the Product At Hilbert's AI, we shorten \"months\" to \"minutes.\" We build the AI Growth Engine that Fortune 500 enterprises and iconic B2C brands use to navigate their revenue drivers in real-time. We are at an inflection point. We are scaling from a \"fast-response\" early-stage team to a multi-department engineering organization (Data & Software Engineering as your department) of 20+ people across San Francisco and Istanbul . We are looking for an Engineering Leader to own the technical heart of Hilbert. You will lead the infrastructure and software that powers our engine, working in parallel with our AI/ML department to turn predictive models into production-grade enterprise outcomes. The Hard Problems: Scale, Systems, and the \"Human Interface\" This role will deliver more than managing people; it's about architecting an organization. You are the bridge between raw data, agentic AI, and the customer experience. Our Current Hurdles: - Multi-Deployment Architecture : Build once and ship consistently across our Cloud SaaS (ClickHouse), enterprise on-prem deployments, and warehouse-native zero-extract model, ensuring a unified experience for engineering and forward-deployed data teams. - The Distributed Engine: Our team is split between SF and Istanbul (an 11-hour gap) . You need to build a high-sync culture that thrives despite the distance, ensuring speed doesn't sacrifice quality. - Building the Roadmap from Scratch: We are in the process of hiring our first Product Managers and Customer Success teams. You will",
      "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"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 8,
      "years_experience_max": 12,
      "role_function": "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.4709b66649eba3921b",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "49e58ae39ff5da27235f92c94434bce6",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:49e58ae39ff5da27235f92c94434bce6:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/hilberts/9356cb85-e325-445e-b4d6-1c80114ec8f0",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/hilberts/9356cb85-e325-445e-b4d6-1c80114ec8f0",
          "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/hilberts/9356cb85-e325-445e-b4d6-1c80114ec8f0",
          "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/hilberts/9356cb85-e325-445e-b4d6-1c80114ec8f0",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "c76137f0e8c9c6c7de367f0699dcb3b0",
      "title": "Senior Backend Engineer, Inference Platform",
      "employer_name": "Together AI",
      "employer_slug": "together-ai",
      "location_text": "San Francisco",
      "country": "US",
      "employment_type": "full_time",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 160000,
      "salary_max": 250000,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": "year",
      "base_salary_min": 160000,
      "base_salary_max": 250000,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "options"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cbinsights_unicorn"
      ],
      "posted_at": "2025-08-22T18:40:32.000Z",
      "apply_url": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior Backend Engineer, Inference Platform San Francisco About the Role Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale. If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You'll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory. You'll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency. - Shape the core inference backbone that powers Together AI's frontier models. - Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation. - Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale. - Partner with world-class researchers to bring new model architectures into production. - Collaborate with and contribute to the open source community, shaping the tools that advance the industry. - A culture of deep technical ownership and high impact - where your work makes models faster, cheaper, and more accessible. - Competitive compensation, equity, and benefits. Responsibilities - Build and optimize global and",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 47,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "contractor_type": {
          "field": "contractor_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "contractor_type"
        },
        "employment_type": {
          "field": "employment_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "employment_type"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "growth-stage",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.838484da4e54d31e41",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "c76137f0e8c9c6c7de367f0699dcb3b0",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:c76137f0e8c9c6c7de367f0699dcb3b0:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "company_stage": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/togetherai/jobs/4835763007",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "9392c64e1b353afe0895616feb5a7c00",
      "title": "Member of Technical Staff",
      "employer_name": "WarpBuild",
      "employer_slug": "warpbuild",
      "location_text": "India | Remote",
      "country": "IN",
      "employment_type": "unknown",
      "remote_status": "remote",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": 0,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "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": [
        "yc"
      ],
      "posted_at": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://jobs.ashbyhq.com/warpbuild/0be04256-b2cc-4756-bc35-d82abc761dfc",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Member of Technical Staff India | Remote WarpBuild provides compute infrastructure and tools for enabling AI-powered teams to work efficiently. We are a small team working on multiple products: WarpBuild CI (blazing fast github actions runners), and Helios (agentic harness for your company's knowledge). As a part of the early team, you'll play a role in everything we do. WHAT YOU'LL BRING - You are an engineer with first-principles thinking and passionate about product and user experience. Customers are at the heart of everything you do. - You have a strong entrepreneurial mindset. You might have been a founder previously, have built an impressive side project or led on a project in our day job. WHAT WE OFFER - High equity and compensation. - High impact role as a founding member of a high growth, profitable startup. - A very wide and interesting set of problems to work on. Bonus: write a poem you wrote and we'll place you in the fast track queue for interviews. ABOUT THE INTERVIEW The process is super quick and consists of 4 rounds. You'll be using your own computer, and using the language/environment with which you are most comfortable. You are encouraged to use AI tools and IDEs for the exercises. You'll be doing a screen share with video during the call. A local env for development is preferred because some exercises might need inter communicating services. The interview process is a deeper dive into technical abilities, product thinking and overall fit. For the",
      "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"
        },
        "remote_status": {
          "field": "remote_status",
          "source": "rule:remote_status",
          "db_column": "remote_status"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "days_in_office": {
          "field": "days_in_office",
          "source": "rule:remote_status",
          "db_column": "days_in_office"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "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": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 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.359b88bad82d10e556",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9392c64e1b353afe0895616feb5a7c00",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Member of Technical Staff India | Remote WarpBuild provides compute infrastructure and tools for enabling AI-powered teams to work efficiently. We are a small team working on multiple products: WarpBuild CI (blazing fast github actions runners), and Helios (agentic harness for your company's knowledge). As a part of the early team, you'll play a role in everything we do. WHAT YOU'LL BRING - You are an engineer with first-principles thinking and passionate about product and user experience. Customers are at the heart of everything you do. - You have a strong entrepreneurial mindset. You might have been a founder previously, have built an impressive side project or led on a project in our day job. WHAT WE OFFER - High equity and compensation. - High impact role as a founding member of a high growth, profitable startup. - A very wide and interesting set of problems to work on. Bonus: write a poem you wrote and we'll place you in the fast track queue for interviews. ABOUT THE INTERVIEW The process is super quick and consists of 4 rounds. You'll be using your own computer, and using the language/environment with which you are most comfortable. You are encouraged to use AI tools and IDEs for the exercises. You'll be doing a screen share with video during the call. A local env for development is preferred because some exercises might need inter communicating services. The interview process is a deeper dive into technical abilities, product thinking and overall fit. For the",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:9392c64e1b353afe0895616feb5a7c00:description:compute",
          "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.4310fe89b566c573ee",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9392c64e1b353afe0895616feb5a7c00",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description matched \"strong\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Member of Technical Staff India | Remote WarpBuild provides compute infrastructure and tools for enabling AI-powered teams to work efficiently. We are a small team working on multiple products: WarpBuild CI (blazing fast github actions runners), and Helios (agentic harness for your company's knowledge). As a part of the early team, you'll play a role in everything we do. WHAT YOU'LL BRING - You are an engineer with first-principles thinking and passionate about product and user experience. Customers are at the heart of everything you do. - You have a strong entrepreneurial mindset. You might have been a founder previously, have built an impressive side project or led on a project in our day job. WHAT WE OFFER - High equity and compensation. - High impact role as a founding member of a high growth, profitable startup. - A very wide and interesting set of problems to work on. Bonus: write a poem you wrote and we'll place you in the fast track queue for interviews. ABOUT THE INTERVIEW The process is super quick and consists of 4 rounds. You'll be using your own computer, and using the language/environment with which you are most comfortable. You are encouraged to use AI tools and IDEs for the exercises. You'll be doing a screen share with video during the call. A local env for development is preferred because some exercises might need inter communicating services. The interview process is a deeper dive into technical abilities, product thinking and overall fit. For the",
          "matched_input": "strong",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:9392c64e1b353afe0895616feb5a7c00:description:strong",
          "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.a60da8f74c07380906",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9392c64e1b353afe0895616feb5a7c00",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Member of Technical Staff India | Remote WarpBuild provides compute infrastructure and tools for enabling AI-powered teams to work efficiently. We are a small team working on multiple products: WarpBuild CI (blazing fast github actions runners), and Helios (agentic harness for your company's knowledge). As a part of the early team, you'll play a role in everything we do. WHAT YOU'LL BRING - You are an engineer with first-principles thinking and passionate about product and user experience. Customers are at the heart of everything you do. - You have a strong entrepreneurial mindset. You might have been a founder previously, have built an impressive side project or led on a project in our day job. WHAT WE OFFER - High equity and compensation. - High impact role as a founding member of a high growth, profitable startup. - A very wide and interesting set of problems to work on. Bonus: write a poem you wrote and we'll place you in the fast track queue for interviews. ABOUT THE INTERVIEW The process is super quick and consists of 4 rounds. You'll be using your own computer, and using the language/environment with which you are most comfortable. You are encouraged to use AI tools and IDEs for the exercises. You'll be doing a screen share with video during the call. A local env for development is preferred because some exercises might need inter communicating services. The interview process is a deeper dive into technical abilities, product thinking and overall fit. For the",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.b9ddf08ec9dbae6b55",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9392c64e1b353afe0895616feb5a7c00",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description contains \"strong\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Member of Technical Staff India | Remote WarpBuild provides compute infrastructure and tools for enabling AI-powered teams to work efficiently. We are a small team working on multiple products: WarpBuild CI (blazing fast github actions runners), and Helios (agentic harness for your company's knowledge). As a part of the early team, you'll play a role in everything we do. WHAT YOU'LL BRING - You are an engineer with first-principles thinking and passionate about product and user experience. Customers are at the heart of everything you do. - You have a strong entrepreneurial mindset. You might have been a founder previously, have built an impressive side project or led on a project in our day job. WHAT WE OFFER - High equity and compensation. - High impact role as a founding member of a high growth, profitable startup. - A very wide and interesting set of problems to work on. Bonus: write a poem you wrote and we'll place you in the fast track queue for interviews. ABOUT THE INTERVIEW The process is super quick and consists of 4 rounds. You'll be using your own computer, and using the language/environment with which you are most comfortable. You are encouraged to use AI tools and IDEs for the exercises. You'll be doing a screen share with video during the call. A local env for development is preferred because some exercises might need inter communicating services. The interview process is a deeper dive into technical abilities, product thinking and overall fit. For the",
          "matched_input": "strong",
          "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://jobs.ashbyhq.com/warpbuild/0be04256-b2cc-4756-bc35-d82abc761dfc",
          "source_values": [
            "rule:remote_status"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/warpbuild/0be04256-b2cc-4756-bc35-d82abc761dfc",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/warpbuild/0be04256-b2cc-4756-bc35-d82abc761dfc",
          "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/warpbuild/0be04256-b2cc-4756-bc35-d82abc761dfc",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "ca0e580089e9c47c93f6400c1349745d",
      "title": "Performance Architect, Use Case and Workload Analysis",
      "employer_name": "Google",
      "employer_slug": "google",
      "location_text": "New Taipei, Banqiao District, New Taipei City, Taiwan; +1 more",
      "country": "TW",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu"
      ],
      "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": "2026-05-21T14:31:34.000Z",
      "apply_url": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
      "apply_url_verified": false,
      "ats": "google_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Performance Architect, Use Case and Workload Analysis New Taipei, Banqiao District, New Taipei City, Taiwan; +1 more Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Conduct CPU power and performance correlation. Conduct CPU workload analysis and optimization on real use cases and commercial benchmarks. Drive post-silicon characterization and failure analysis for next-generation CPU and memory systems, focusing on optimizing F_max/V_min boundaries and root-causing complex silicon-level bugs. Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience. 4 years of experience in embedded system software development, test and debugging. Experience in programming (e.g., Python, or C/C++, Shell script). Experience with Android/Linux environments. Preferred qualifications: Experience in silicon characterization, system-level test (SLT), chip bring-up, hardware debugging, and failure analysis (FA). Expertise in performance and power analysis for CPUs, GPUs, TPUs, interconnect fabrics, and memory systems, including QoS tuning and bandwidth/latency analysis. Knowledge of OS kernel-level optimization, including schedulers,",
      "parental_leave_weeks": 18,
      "non_birth_parent_leave_weeks": 18,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 90,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/",
          "db_column": "parental_leave_weeks",
          "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 4,
      "years_experience_max": 8,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.66f700e3e6b39d3fb1",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "ca0e580089e9c47c93f6400c1349745d",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Performance Architect, Use Case and Workload Analysis New Taipei, Banqiao District, New Taipei City, Taiwan; +1 more Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Conduct CPU power and performance correlation. Conduct CPU workload analysis and optimization on real use cases and commercial benchmarks. Drive post-silicon characterization and failure analysis for next-generation CPU and memory systems, focusing on optimizing F_max/V_min boundaries and root-causing complex silicon-level bugs. Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience. 4 years of experience in embedded system software development, test and debugging. Experience in programming (e.g., Python, or C/C++, Shell script). Experience with Android/Linux environments. Preferred qualifications: Experience in silicon characterization, system-level test (SLT), chip bring-up, hardware debugging, and failure analysis (FA). Expertise in performance and power analysis for CPUs, GPUs, TPUs, interconnect fabrics, and memory systems, including QoS tuning and bandwidth/latency analysis. Knowledge of OS kernel-level optimization, including schedulers,",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.759e4d5d6d58eb8486",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "ca0e580089e9c47c93f6400c1349745d",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:ca0e580089e9c47c93f6400c1349745d:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
          "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/1652044/000165204426000018/goog-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
          "source_values": [
            "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
          "source_values": [
            "https://blog.google/company-news/outreach-and-initiatives/diversity/international-womens-day-2022/"
          ],
          "checked_at": "2026-05-07"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-05-07"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.google.com/about/careers/applications/signin?jobId=CiUAL2FckYpvL4mtIbm0jlQqWAbSQXsWgl4kATNKnTubLHhLfkjXEjsACxwdTHoMBTAhM8hgxlLg8ytVVcozQoMW2tuy_6QjKVSOR4ZpGQeZj4THD82l25NY09QR5rXoKP1mag%3D%3D_V2&loc=TW&title=Performance+Architect",
          "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": "08d39dcdc9fe6c89210a80e83decde14",
      "title": "Computer Vision Engineer, Senior",
      "employer_name": "9 Mothers",
      "employer_slug": "9-mothers",
      "location_text": "Austin | OnSite",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "onsite",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": 5,
      "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": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://jobs.ashbyhq.com/9-mothers/fd8c2655-efe2-490e-bff8-e8fed5dbf9aa",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Computer Vision Engineer, Senior Austin | OnSite LOCATION: ONSITE - AUSTIN, TX Employment Type: Direct Hire, Full‑Time Job Title: Senior Computer Vision Engineer Company Overview 9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. Our first product, EDDA, is an autonomous counter-sUAS point-defense platform designed to detect, track, and neutralize Group 1 drone threats. The company is headquartered in Austin, Texas. Position Summary We are seeking a Senior Computer Vision Engineer to serve as the “eyes” of our autonomous c-sUAS platforms. You will design, implement, and optimize the entire perception pipeline, specializing in low-latency, high-frame-rate processing to track small, fast objects with zero margin for error. You should be comfortable building models and systems from the ground up, moving beyond simply utilizing existing frameworks. Essential Duties - Architect and Implement: Develop the entire embedded CV pipeline using high-performance Python and C++. - Target Tracking & Sensor Fusion: Design and deploy robust multi-object tracking and sensor fusion algorithms to ensure high-fidelity state estimation of fast-moving targets. - Object Detection: Utilize real-time models (e.g., YOLO) and CNNs optimized for speed. - Embedded Optimization: Optimize code for low-latency performance on resource-constrained NVIDIA Jetson environments using libraries like TensorRT and TFLite. - Geometric Vision: Apply principles of calibration, rectification, and 3D geometry to translate 2D footage into accurate 3D coordinates for fire control. - Cross-Functional Collaboration: Work with robotics teams to ensure perception data is reliable for autonomous decision-making. Requirements - Programming: Strong background in C++ (for performance) or Python. - SLAM/Localization:",
      "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": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 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.5053814fb7159af570",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "08d39dcdc9fe6c89210a80e83decde14",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description matched \"strong\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Computer Vision Engineer, Senior Austin | OnSite LOCATION: ONSITE - AUSTIN, TX Employment Type: Direct Hire, Full‑Time Job Title: Senior Computer Vision Engineer Company Overview 9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. Our first product, EDDA, is an autonomous counter-sUAS point-defense platform designed to detect, track, and neutralize Group 1 drone threats. The company is headquartered in Austin, Texas. Position Summary We are seeking a Senior Computer Vision Engineer to serve as the “eyes” of our autonomous c-sUAS platforms. You will design, implement, and optimize the entire perception pipeline, specializing in low-latency, high-frame-rate processing to track small, fast objects with zero margin for error. You should be comfortable building models and systems from the ground up, moving beyond simply utilizing existing frameworks. Essential Duties - Architect and Implement: Develop the entire embedded CV pipeline using high-performance Python and C++. - Target Tracking & Sensor Fusion: Design and deploy robust multi-object tracking and sensor fusion algorithms to ensure high-fidelity state estimation of fast-moving targets. - Object Detection: Utilize real-time models (e.g., YOLO) and CNNs optimized for speed. - Embedded Optimization: Optimize code for low-latency performance on resource-constrained NVIDIA Jetson environments using libraries like TensorRT and TFLite. - Geometric Vision: Apply principles of calibration, rectification, and 3D geometry to translate 2D footage into accurate 3D coordinates for fire control. - Cross-Functional Collaboration: Work with robotics teams to ensure perception data is reliable for autonomous decision-making. Requirements - Programming: Strong background in C++ (for performance) or Python. - SLAM/Localization:",
          "matched_input": "strong",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:08d39dcdc9fe6c89210a80e83decde14:description:strong",
          "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.8ce86eca9b77e5daac",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "08d39dcdc9fe6c89210a80e83decde14",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Computer Vision Engineer, Senior Austin | OnSite LOCATION: ONSITE - AUSTIN, TX Employment Type: Direct Hire, Full‑Time Job Title: Senior Computer Vision Engineer Company Overview 9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. Our first product, EDDA, is an autonomous counter-sUAS point-defense platform designed to detect, track, and neutralize Group 1 drone threats. The company is headquartered in Austin, Texas. Position Summary We are seeking a Senior Computer Vision Engineer to serve as the “eyes” of our autonomous c-sUAS platforms. You will design, implement, and optimize the entire perception pipeline, specializing in low-latency, high-frame-rate processing to track small, fast objects with zero margin for error. You should be comfortable building models and systems from the ground up, moving beyond simply utilizing existing frameworks. Essential Duties - Architect and Implement: Develop the entire embedded CV pipeline using high-performance Python and C++. - Target Tracking & Sensor Fusion: Design and deploy robust multi-object tracking and sensor fusion algorithms to ensure high-fidelity state estimation of fast-moving targets. - Object Detection: Utilize real-time models (e.g., YOLO) and CNNs optimized for speed. - Embedded Optimization: Optimize code for low-latency performance on resource-constrained NVIDIA Jetson environments using libraries like TensorRT and TFLite. - Geometric Vision: Apply principles of calibration, rectification, and 3D geometry to translate 2D footage into accurate 3D coordinates for fire control. - Cross-Functional Collaboration: Work with robotics teams to ensure perception data is reliable for autonomous decision-making. Requirements - Programming: Strong background in C++ (for performance) or Python. - SLAM/Localization:",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:08d39dcdc9fe6c89210a80e83decde14:description:compute",
          "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.24d2f46b8355e1b74c",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "08d39dcdc9fe6c89210a80e83decde14",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Computer Vision Engineer, Senior",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:08d39dcdc9fe6c89210a80e83decde14:title:compute",
          "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.4e7edcec51fec861d6",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "08d39dcdc9fe6c89210a80e83decde14",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description contains \"strong\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Computer Vision Engineer, Senior Austin | OnSite LOCATION: ONSITE - AUSTIN, TX Employment Type: Direct Hire, Full‑Time Job Title: Senior Computer Vision Engineer Company Overview 9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. Our first product, EDDA, is an autonomous counter-sUAS point-defense platform designed to detect, track, and neutralize Group 1 drone threats. The company is headquartered in Austin, Texas. Position Summary We are seeking a Senior Computer Vision Engineer to serve as the “eyes” of our autonomous c-sUAS platforms. You will design, implement, and optimize the entire perception pipeline, specializing in low-latency, high-frame-rate processing to track small, fast objects with zero margin for error. You should be comfortable building models and systems from the ground up, moving beyond simply utilizing existing frameworks. Essential Duties - Architect and Implement: Develop the entire embedded CV pipeline using high-performance Python and C++. - Target Tracking & Sensor Fusion: Design and deploy robust multi-object tracking and sensor fusion algorithms to ensure high-fidelity state estimation of fast-moving targets. - Object Detection: Utilize real-time models (e.g., YOLO) and CNNs optimized for speed. - Embedded Optimization: Optimize code for low-latency performance on resource-constrained NVIDIA Jetson environments using libraries like TensorRT and TFLite. - Geometric Vision: Apply principles of calibration, rectification, and 3D geometry to translate 2D footage into accurate 3D coordinates for fire control. - Cross-Functional Collaboration: Work with robotics teams to ensure perception data is reliable for autonomous decision-making. Requirements - Programming: Strong background in C++ (for performance) or Python. - SLAM/Localization:",
          "matched_input": "strong",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.title.fe561758af9164b4d1",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "08d39dcdc9fe6c89210a80e83decde14",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Computer Vision Engineer, Senior",
          "matched_input": "compute",
          "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://jobs.ashbyhq.com/9-mothers/fd8c2655-efe2-490e-bff8-e8fed5dbf9aa",
          "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/9-mothers/fd8c2655-efe2-490e-bff8-e8fed5dbf9aa",
          "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/9-mothers/fd8c2655-efe2-490e-bff8-e8fed5dbf9aa",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "9a696e79d2fb342828848184b7837281",
      "title": "Senior Solutions Architect, AI Compute – NPN",
      "employer_name": "NVIDIA Corporation",
      "employer_slug": "nvidia",
      "location_text": "6 Locations",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "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": "2026-06-06T00:00:00.000Z",
      "apply_url": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Remote/Senior-Solutions-Architect--AI-Compute----NPN_JR2015936",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior Solutions Architect, AI Compute – NPN 6 Locations posted: Posted 6 Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.title.5e813b20bdea64d405",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9a696e79d2fb342828848184b7837281",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Senior Solutions Architect, AI Compute – NPN",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.c3998cce524ebb4bcd",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "9a696e79d2fb342828848184b7837281",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:9a696e79d2fb342828848184b7837281:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Remote/Senior-Solutions-Architect--AI-Compute----NPN_JR2015936",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Remote/Senior-Solutions-Architect--AI-Compute----NPN_JR2015936",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "19578d191e0a7467eba1302d0598e602",
      "title": "Photonics Design Engineer - Computational Photonics",
      "employer_name": "Xanadu",
      "employer_slug": "xanadu",
      "location_text": "Location not specified",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": 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": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://xanadu.jazz.co/apply/Rgpk5l7ipz/Photonics-Design-Engineer-Computational-Photonics",
      "apply_url_verified": false,
      "ats": "jazzhr",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Photonics Design Engineer - Computational Photonics Photonics Design Engineer - Computational Photonics",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://xanadu.jazz.co/apply/Rgpk5l7ipz/Photonics-Design-Engineer-Computational-Photonics",
          "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://xanadu.jazz.co/apply/Rgpk5l7ipz/Photonics-Design-Engineer-Computational-Photonics",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "0e7aea57c74199e15d1104d9967553e3",
      "title": "Computer Engineering Intern (SQE Team)",
      "employer_name": "Seagate Technology",
      "employer_slug": "seagate-technology",
      "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": 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": "2026-06-12T10:25:24.000Z",
      "apply_url": "https://seagatecareers.com/job/Samut-Prakan-Computer-Engineering-Intern-%28SQE-Team%29/1399255700/",
      "apply_url_verified": false,
      "ats": "custom_structured",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Computer Engineering Intern (SQE Team) Computer Engineering Intern (SQE Team)",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1137789/000113778925000157/stx-20250627.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"
        },
        "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/1137789/000113778925000157/stx-20250627.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "entry",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 0,
      "years_experience_max": 4,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.08559211370a344b38",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "0e7aea57c74199e15d1104d9967553e3",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Computer Engineering Intern (SQE Team) Computer Engineering Intern (SQE Team)",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:0e7aea57c74199e15d1104d9967553e3:description:compute",
          "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.905c5995295f853955",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "0e7aea57c74199e15d1104d9967553e3",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Computer Engineering Intern (SQE Team)",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:0e7aea57c74199e15d1104d9967553e3:title:compute",
          "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.362e8642b6151b597b",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "0e7aea57c74199e15d1104d9967553e3",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Computer Engineering Intern (SQE Team)",
          "matched_input": "compute",
          "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": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1137789/000113778925000157/stx-20250627.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1137789/000113778925000157/stx-20250627.htm"
          ],
          "checked_at": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://seagatecareers.com/job/Samut-Prakan-Computer-Engineering-Intern-%28SQE-Team%29/1399255700/",
          "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://seagatecareers.com/job/Samut-Prakan-Computer-Engineering-Intern-%28SQE-Team%29/1399255700/",
          "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": "228494dd0ae56816225597bde6a8d6a7",
      "title": "Principal Machine Learning Engineer",
      "employer_name": "Physicsx",
      "employer_slug": "physicsx",
      "location_text": "Singapore",
      "country": "SG",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": 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": [
        "generalcatalyst"
      ],
      "posted_at": "2026-01-11T22:16:02.000Z",
      "apply_url": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4749999101",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Principal Machine Learning Engineer Singapore About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Who We're Looking For As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years industry experience (post Masters or PhD) in a commercial, non-research",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "principal",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 12,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "doctorate",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.e73df23f5a7559d78b",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "228494dd0ae56816225597bde6a8d6a7",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:228494dd0ae56816225597bde6a8d6a7:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4749999101",
          "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.eu.greenhouse.io/physicsx/jobs/4749999101",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "5df3a2485572eaac305b298d60609e24",
      "title": "Strategic Projects Lead, Coding",
      "employer_name": "Handshake",
      "employer_slug": "handshake",
      "location_text": "India, Bengaluru, Karnataka",
      "country": "IN",
      "employment_type": "full_time",
      "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": "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": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": true,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cbinsights_unicorn",
        "sequoia"
      ],
      "posted_at": "2026-05-29T19:12:16.461Z",
      "apply_url": "https://jobs.ashbyhq.com/handshake/1f996bb7-53b5-4150-be1e-4bdf183b83dc",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Strategic Projects Lead, Coding India, Bengaluru, Karnataka About Handshake Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We've grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world's top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. We are building our India team",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "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"
        },
        "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"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 4,
      "years_experience_max": 8,
      "role_function": "operations",
      "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": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.4d8699d90573122bf4",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "5df3a2485572eaac305b298d60609e24",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:5df3a2485572eaac305b298d60609e24:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/handshake/1f996bb7-53b5-4150-be1e-4bdf183b83dc",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/handshake/1f996bb7-53b5-4150-be1e-4bdf183b83dc",
          "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/handshake/1f996bb7-53b5-4150-be1e-4bdf183b83dc",
          "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/handshake/1f996bb7-53b5-4150-be1e-4bdf183b83dc",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "ccb2773c2ffce1adb24620d3d128dc0a",
      "title": "End User Computing Support Analyst",
      "employer_name": "Paylocity",
      "employer_slug": "paylocity",
      "location_text": "Guadalajara, Mexico",
      "country": "MX",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "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": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://2000recruiting.paylocity.com/recruiting/jobs/Apply/44430/Paylocity/End-User-Computing-Support-Analyst",
      "apply_url_verified": false,
      "ats": "custom_structured",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "End User Computing Support Analyst Guadalajara, Mexico End User Computing Support Analyst",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1591698/000159169825000087/pcty-20250630.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1591698/000159169825000087/pcty-20250630.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "other",
      "role_function_source": "unknown",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [],
      "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/1591698/000159169825000087/pcty-20250630.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1591698/000159169825000087/pcty-20250630.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://2000recruiting.paylocity.com/recruiting/jobs/Apply/44430/Paylocity/End-User-Computing-Support-Analyst",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "18ba344446b6ded08eb19d351eb27ca2",
      "title": "Software Engineer, Machine Learning/AI Accelerator",
      "employer_name": "Waymo",
      "employer_slug": "waymo",
      "location_text": "Taipei, Taiwan; Hsinchu, Taiwan",
      "country": "TW",
      "employment_type": "full_time",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": 2600000,
      "salary_max": 3150000,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "TWD",
      "salary_type": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": "year",
      "base_salary_min": 2600000,
      "base_salary_max": 3150000,
      "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": [
        "a16z",
        "sequoia"
      ],
      "posted_at": "2026-02-04T22:45:02.000Z",
      "apply_url": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Software Engineer, Machine Learning/AI Accelerator Taipei, Taiwan; Hsinchu, Taiwan Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver™-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle's software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world's highest performance automotive compute platforms. This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Compute team. You will: - Design and implement full stack solution from firmware, low-level drivers, APIs for ML accelerator chips",
      "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": "2026-06-20T23:34:01.980Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "bonus_offered": {
          "field": "bonus_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "bonus_offered"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "contractor_type": {
          "field": "contractor_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "contractor_type"
        },
        "employment_type": {
          "field": "employment_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "employment_type"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "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": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.a318e32e6bab6e8d3b",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "18ba344446b6ded08eb19d351eb27ca2",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Software Engineer, Machine Learning/AI Accelerator Taipei, Taiwan; Hsinchu, Taiwan Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver™-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle's software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world's highest performance automotive compute platforms. This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Compute team. You will: - Design and implement full stack solution from firmware, low-level drivers, APIs for ML accelerator chips",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.f20ceda235be3ddbd2",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "18ba344446b6ded08eb19d351eb27ca2",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:18ba344446b6ded08eb19d351eb27ca2:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        },
        "company_stage": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.withwaymo.com/jobs?gh_jid=7584885",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T23:34:01.980Z"
        }
      }
    },
    {
      "id": "b1c3ac8346445306dd7ff4f776daf08b",
      "title": "Sr. Applied Scientist, Agentic Automated Reasoning Group",
      "employer_name": "Amazon",
      "employer_slug": "amazon",
      "location_text": "Boston, Massachusetts, USA",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 167100,
      "salary_max": 226100,
      "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": 167100,
      "base_salary_max": 226100,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": true,
      "childcare_subsidy": true,
      "fertility_family_building_benefits": true,
      "adoption_assistance_offered": true,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-15T00:00:00.000Z",
      "apply_url": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
      "apply_url_verified": false,
      "ats": "amazon_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Sr. Applied Scientist, Agentic Automated Reasoning Group Boston, Massachusetts, USA The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavor. The Strata team (https://github.com/strata-org) is seeking a Sr. Applied Scientist with broad interest and expertise in interactive theorem proving, programming language semantics, deductive verification and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities - End-to-end technical leadership for delivering AR solutions working backwards customer use cases. - Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required. - Use tools spanning from fuzzers, property-based testing to model checkers, and interactive theorem provers",
      "parental_leave_weeks": 6,
      "non_birth_parent_leave_weeks": 6,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 56,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "childcare_subsidy": {
          "field": "childcare_subsidy",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "childcare_subsidy"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families",
          "db_column": "parental_leave_weeks",
          "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families"
        },
        "mental_health_support": {
          "field": "mental_health_support",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "mental_health_support"
        },
        "adoption_assistance_offered": {
          "field": "adoption_assistance_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "adoption_assistance_offered"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "non_birth_parent_leave_weeks"
        },
        "fertility_family_building_benefits": {
          "field": "fertility_family_building_benefits",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "fertility_family_building_benefits"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": "Industrial",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 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.4039a05d11e95866b5",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "b1c3ac8346445306dd7ff4f776daf08b",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:b1c3ac8346445306dd7ff4f776daf08b:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "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/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "company_stage": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "fertility_family_building_benefits": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "mental_health_support": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "adoption_assistance_offered": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "childcare_subsidy": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10421621/sr-applied-scientist-agentic-automated-reasoning-group",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        }
      }
    },
    {
      "id": "a16d26a516b8889b9900536a8a895ea3",
      "title": "Applied Science Manager, Center for Quantum Computing",
      "employer_name": "Amazon",
      "employer_slug": "amazon",
      "location_text": "San Francisco, California, USA",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 211400,
      "salary_max": 286000,
      "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": 211400,
      "base_salary_max": 286000,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": true,
      "childcare_subsidy": true,
      "fertility_family_building_benefits": true,
      "adoption_assistance_offered": true,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-04-23T00:00:00.000Z",
      "apply_url": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
      "apply_url_verified": false,
      "ats": "amazon_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Applied Science Manager, Center for Quantum Computing San Francisco, California, USA Do you want to make an impact on quantum computing hardware development through computational science and engineering? Do you thrive when working with scientists and engineers from diverse backgrounds in a multidisciplinary environment? The Amazon Center for Quantum Computing (CQC) is seeking to hire an Applied Science Manager to innovate in physical design and simulation methods, and develop the software stack used to design superconducting quantum computers. In this role, you will lead a team developing scientific software for quantum electronic design automation. The ideal candidate is expected to advance the state of the art for computational science in service of realizing a fault-tolerant quantum computer. Key job responsibilities - Hire and develop Applied Scientists that build physical design and simulation software - Partner with science teams to understand needs and drive adoption of improved methods and tooling - Influence engineering team development priorities in high-performance computing infrastructure - Manage tactical and strategic initiatives with scientific projects pursued within team - Enable creative and innovative experimentation while striving for operational excellence About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our",
      "parental_leave_weeks": 6,
      "non_birth_parent_leave_weeks": 6,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 56,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "childcare_subsidy": {
          "field": "childcare_subsidy",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "childcare_subsidy"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families",
          "db_column": "parental_leave_weeks",
          "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families"
        },
        "mental_health_support": {
          "field": "mental_health_support",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "mental_health_support"
        },
        "us_citizenship_required": {
          "field": "us_citizenship_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "us_citizenship_required"
        },
        "adoption_assistance_offered": {
          "field": "adoption_assistance_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "adoption_assistance_offered"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "non_birth_parent_leave_weeks"
        },
        "fertility_family_building_benefits": {
          "field": "fertility_family_building_benefits",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "fertility_family_building_benefits"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 9,
      "role_function": "data",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Industrial",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": true,
      "security_clearance": "none",
      "education_required": "doctorate",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.fc1087ca82eb7d83d6",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "a16d26a516b8889b9900536a8a895ea3",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Applied Science Manager, Center for Quantum Computing San Francisco, California, USA Do you want to make an impact on quantum computing hardware development through computational science and engineering? Do you thrive when working with scientists and engineers from diverse backgrounds in a multidisciplinary environment? The Amazon Center for Quantum Computing (CQC) is seeking to hire an Applied Science Manager to innovate in physical design and simulation methods, and develop the software stack used to design superconducting quantum computers. In this role, you will lead a team developing scientific software for quantum electronic design automation. The ideal candidate is expected to advance the state of the art for computational science in service of realizing a fault-tolerant quantum computer. Key job responsibilities - Hire and develop Applied Scientists that build physical design and simulation software - Partner with science teams to understand needs and drive adoption of improved methods and tooling - Influence engineering team development priorities in high-performance computing infrastructure - Manage tactical and strategic initiatives with scientific projects pursued within team - Enable creative and innovative experimentation while striving for operational excellence About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:a16d26a516b8889b9900536a8a895ea3:description:compute",
          "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.d5760e06b06fd78518",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "a16d26a516b8889b9900536a8a895ea3",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Applied Science Manager, Center for Quantum Computing San Francisco, California, USA Do you want to make an impact on quantum computing hardware development through computational science and engineering? Do you thrive when working with scientists and engineers from diverse backgrounds in a multidisciplinary environment? The Amazon Center for Quantum Computing (CQC) is seeking to hire an Applied Science Manager to innovate in physical design and simulation methods, and develop the software stack used to design superconducting quantum computers. In this role, you will lead a team developing scientific software for quantum electronic design automation. The ideal candidate is expected to advance the state of the art for computational science in service of realizing a fault-tolerant quantum computer. Key job responsibilities - Hire and develop Applied Scientists that build physical design and simulation software - Partner with science teams to understand needs and drive adoption of improved methods and tooling - Influence engineering team development priorities in high-performance computing infrastructure - Manage tactical and strategic initiatives with scientific projects pursued within team - Enable creative and innovative experimentation while striving for operational excellence About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "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/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "fertility_family_building_benefits": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "mental_health_support": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "adoption_assistance_offered": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "childcare_subsidy": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.amazon.jobs/en/jobs/10401537/applied-science-manager-center-for-quantum-computing",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        }
      }
    },
    {
      "id": "ae5562d78b8edc7eb96a4e6577f09274",
      "title": "Computer Vision and Machine Learning Engineer",
      "employer_name": "Apple",
      "employer_slug": "apple",
      "location_text": "Sunnyvale, United States of America",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 147400,
      "salary_max": 272100,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": "year",
      "base_salary_min": 147400,
      "base_salary_max": 272100,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2025-01-08T01:16:56.756Z",
      "apply_url": "https://jobs.apple.com/en-us/details/200585934/computer-vision-and-machine-learning-engineer?team=MLAI",
      "apply_url_verified": false,
      "ats": "apple_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Computer Vision and Machine Learning Engineer Sunnyvale, United States of America The Video Computer Vision org is a centralized applied research and engineering team responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We have contributed to the algorithms driving FaceID and FaceKit in the past and more recently to the new Apple Vision Pro and Spatial Computing. As a member of the Video Computer Vision group you will perform cutting-edge artificial intelligence research that will craft the future of spatial computing. We are looking for the right 3D Computer Vision and Machine Learning Engineer to help us take our efforts to the next level. You will be part of a community of researchers and engineers who are passionate about pushing the boundaries of what is possible with spatial media and AI. We value a culture of learning, intellectual curiosity, and exploration, and we believe that your passion and expertise will help us create revolutionary products that delight and inspire millions of people every day. We are looking for a proactive Computer Vision and Machine Learning Engineer to join our team and help design and implement algorithms for spatial media and AI. The ideal candidate should have experience with 3DCV, rendering techniques and machine learning and be passionate about bringing algorithms from research all the way to product. In this position, you will work along side computer vision and machine learning researchers to implement world class algorithms that pushes the state of the art and",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 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"
        },
        "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": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.496467417c562cf41e",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "ae5562d78b8edc7eb96a4e6577f09274",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Computer Vision and Machine Learning Engineer Sunnyvale, United States of America The Video Computer Vision org is a centralized applied research and engineering team responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We have contributed to the algorithms driving FaceID and FaceKit in the past and more recently to the new Apple Vision Pro and Spatial Computing. As a member of the Video Computer Vision group you will perform cutting-edge artificial intelligence research that will craft the future of spatial computing. We are looking for the right 3D Computer Vision and Machine Learning Engineer to help us take our efforts to the next level. You will be part of a community of researchers and engineers who are passionate about pushing the boundaries of what is possible with spatial media and AI. We value a culture of learning, intellectual curiosity, and exploration, and we believe that your passion and expertise will help us create revolutionary products that delight and inspire millions of people every day. We are looking for a proactive Computer Vision and Machine Learning Engineer to join our team and help design and implement algorithms for spatial media and AI. The ideal candidate should have experience with 3DCV, rendering techniques and machine learning and be passionate about bringing algorithms from research all the way to product. In this position, you will work along side computer vision and machine learning researchers to implement world class algorithms that pushes the state of the art and",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:ae5562d78b8edc7eb96a4e6577f09274:description:compute",
          "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.0ce6f22d29b9b816a5",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "ae5562d78b8edc7eb96a4e6577f09274",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Computer Vision and Machine Learning Engineer",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:ae5562d78b8edc7eb96a4e6577f09274:title:compute",
          "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.220e651f632f996aa0",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "ae5562d78b8edc7eb96a4e6577f09274",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Computer Vision and Machine Learning Engineer",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200585934/computer-vision-and-machine-learning-engineer?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/200585934/computer-vision-and-machine-learning-engineer?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/200585934/computer-vision-and-machine-learning-engineer?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/200585934/computer-vision-and-machine-learning-engineer?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/200585934/computer-vision-and-machine-learning-engineer?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": "8998460b137938544a548353cdefa382",
      "title": "AI Workload and Networking Research Architect",
      "employer_name": "NVIDIA Corporation",
      "employer_slug": "nvidia",
      "location_text": "2 Locations",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-27T00:00:00.000Z",
      "apply_url": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Yokneam/AI-Workload-and-Networking-Research-Architect_JR2018707",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "AI Workload and Networking Research Architect 2 Locations posted: Posted 16 Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.516efbf6b071eccf2c",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "8998460b137938544a548353cdefa382",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:8998460b137938544a548353cdefa382:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Yokneam/AI-Workload-and-Networking-Research-Architect_JR2018707",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Yokneam/AI-Workload-and-Networking-Research-Architect_JR2018707",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "8e505696cf7036154fbfe703aac26097",
      "title": "Senior AI Formal Verification Engineer",
      "employer_name": "NVIDIA Corporation",
      "employer_slug": "nvidia",
      "location_text": "3 Locations",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-12T00:00:00.000Z",
      "apply_url": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-AI-Formal-Verification-Engineer_JR2014840",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior AI Formal Verification Engineer 3 Locations posted: Posted 30+ Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.4991b2e97452238c9c",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "8e505696cf7036154fbfe703aac26097",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:8e505696cf7036154fbfe703aac26097:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-AI-Formal-Verification-Engineer_JR2014840",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Israel-Tel-Aviv/Senior-AI-Formal-Verification-Engineer_JR2014840",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "10acec96a1c5aed678eb1844c03c5823",
      "title": "Lead Computer Vision (3D/Optimization) - Paris 🇫🇷",
      "employer_name": "Dental Monitoring",
      "employer_slug": "dental-monitoring",
      "location_text": "Paris, France",
      "country": "FR",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": 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": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://dentalmonitoring.bamboohr.com/careers/950",
      "apply_url_verified": false,
      "ats": "bamboohr",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Lead Computer Vision (3D/Optimization) - Paris 🇫🇷 Paris, France Lead Computer Vision (3D/Optimization) - Paris 🇫🇷",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.757dd89ed81b0b9b66",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "10acec96a1c5aed678eb1844c03c5823",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Lead Computer Vision (3D/Optimization) - Paris 🇫🇷 Paris, France Lead Computer Vision (3D/Optimization) - Paris 🇫🇷",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:10acec96a1c5aed678eb1844c03c5823:description:compute",
          "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.ddfa31667cac7d866e",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "10acec96a1c5aed678eb1844c03c5823",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Lead Computer Vision (3D/Optimization) - Paris 🇫🇷",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:10acec96a1c5aed678eb1844c03c5823:title:compute",
          "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.64bc2c1f625f28b6ec",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "10acec96a1c5aed678eb1844c03c5823",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Lead Computer Vision (3D/Optimization) - Paris 🇫🇷",
          "matched_input": "compute",
          "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": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://dentalmonitoring.bamboohr.com/careers/950",
          "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://dentalmonitoring.bamboohr.com/careers/950",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "2b661a8edc7fbfadd27856b02b7e5d4c",
      "title": "Machine Learning Engineer",
      "employer_name": "Physicsx",
      "employer_slug": "physicsx",
      "location_text": "New York, United States",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 150000,
      "salary_max": 190000,
      "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": 150000,
      "base_salary_max": 190000,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "options"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "generalcatalyst"
      ],
      "posted_at": "2026-04-23T20:11:11.000Z",
      "apply_url": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Machine Learning Engineer New York, United States About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals. Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 2 years industry experience (post",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 47,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 2,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": true,
      "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.0178779513a557bfc9",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "2b661a8edc7fbfadd27856b02b7e5d4c",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:2b661a8edc7fbfadd27856b02b7e5d4c:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101",
          "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.eu.greenhouse.io/physicsx/jobs/4849382101",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "5b689a0e55e21c1c6ea372923623c584",
      "title": "Optical - Computer Vision Engineer - Paris 🇫🇷",
      "employer_name": "Dental Monitoring",
      "employer_slug": "dental-monitoring",
      "location_text": "Paris, France",
      "country": "FR",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": 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": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://dentalmonitoring.bamboohr.com/careers/991",
      "apply_url_verified": false,
      "ats": "bamboohr",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Optical - Computer Vision Engineer - Paris 🇫🇷 Paris, France Optical - Computer Vision Engineer - Paris 🇫🇷",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.6c445d6517b9eba81d",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "5b689a0e55e21c1c6ea372923623c584",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Optical - Computer Vision Engineer - Paris 🇫🇷 Paris, France Optical - Computer Vision Engineer - Paris 🇫🇷",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:5b689a0e55e21c1c6ea372923623c584:description:compute",
          "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.8fd223f26066663c79",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "5b689a0e55e21c1c6ea372923623c584",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Optical - Computer Vision Engineer - Paris 🇫🇷",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:5b689a0e55e21c1c6ea372923623c584:title:compute",
          "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.3d2575cf2e2ff80a9a",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "5b689a0e55e21c1c6ea372923623c584",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Optical - Computer Vision Engineer - Paris 🇫🇷",
          "matched_input": "compute",
          "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": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://dentalmonitoring.bamboohr.com/careers/991",
          "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://dentalmonitoring.bamboohr.com/careers/991",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "25ce0faaa45f3edd87b486324f26b728",
      "title": "Senior Platform Engineer - Compute",
      "employer_name": "Feedzai",
      "employer_slug": "feedzai",
      "location_text": "Portugal",
      "country": "PT",
      "employment_type": "contract",
      "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": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cbinsights_unicorn"
      ],
      "posted_at": "2026-06-02T14:59:40.000Z",
      "apply_url": "https://careers.feedzai.com/job_description?gh_jid=7976688",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior Platform Engineer - Compute Portugal Feedzai is the world's first RiskOps platform for financial risk management, and the market leader in safeguarding global commerce with today's most advanced cloud-based risk management platform, powered by machine learning and artificial intelligence. Feedzai is securing the transition to a cashless world while enabling digital trust in every transaction and payment type. The world's largest banks, processors, and retailers trust Feedzai to protect trillions of dollars and manage risk while improving the customer experience for everyday users, without compromising privacy. Feedzai is a Series D company and has raised $282M to date. With a valuation of $2 billion, our technology protects 1 billion consumers and 90 billion transactions each year. With Cloud at its core, the Engineering (Tech) Team is responsible for all Feedzai product development. Together with Product Management and Data Science, we build the next generation of tools to catch fraud in real-time with a machine learning first approach. Formed by engineers and managed by engineers, at Feedzai, you will find one of the most talented teams out there, from junior to senior engineers. We are fast-paced and provide a safe, open, and collaborative environment that encourages us to lean in, try new things and discover our potential with continuous learning for everyone. While building the best value for our customers, you will work with a wide range of technical challenges. Such as building distributed systems that need to operate 24/7 and ultra-low latencies, solving UI/UX problems to help fraud analysts",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "employment_type": {
          "field": "employment_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "employment_type"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "growth-stage",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.title.4d5a17cb590bb8fdf7",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "25ce0faaa45f3edd87b486324f26b728",
          "signal_type": "query_match",
          "display_text": "Title: \"compute\"",
          "tooltip": "Title contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Senior Platform Engineer - Compute",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.cc0b5b120582cf5910",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "25ce0faaa45f3edd87b486324f26b728",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:25ce0faaa45f3edd87b486324f26b728:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://careers.feedzai.com/job_description?gh_jid=7976688",
          "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.feedzai.com/job_description?gh_jid=7976688",
          "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.feedzai.com/job_description?gh_jid=7976688",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "04142bb145fc29907a531d701405280d",
      "title": "Sr Engineering Program Manager, AI/ML",
      "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": 141800,
      "salary_max": 258600,
      "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": 141800,
      "base_salary_max": 258600,
      "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": "2026-05-06T22:51:30.226Z",
      "apply_url": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
      "apply_url_verified": false,
      "ats": "apple_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Sr Engineering Program Manager, AI/ML Cupertino, United States of America At Apple, we believe excellent ideas have a way of becoming extraordinary products with unique customer experiences at the highest quality. When you bring passion and dedication to your job, there's no telling what you could accomplish! The people here at Apple don't just build products - they craft the kind of wonder that's revolutionized entire industries. The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help shape the future of scalable machine learning infrastructure. In this role, you'll lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple's cloud and distributed environments. You'll help define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. We are looking for an energetic and motivated individual with strong communication, organizational, and technical skills who thrives in a fast-paced, dynamic environment. We're looking for a strong Engineering Program Manager with a proven record of building and maintaining complex software platforms, tools, and processes that deliver new end-to-end experiences on-device. You will partner with teams across Apple and deliver some of the most ambitious capabilities for executing AI/ML features on scalable distributed systems, and ensuring reliability, scalability, and efficiency of ML pipelines and services. If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership,",
      "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"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "operations",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "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": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.3983cf80ad363bde24",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "04142bb145fc29907a531d701405280d",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description matched \"strong\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Sr Engineering Program Manager, AI/ML Cupertino, United States of America At Apple, we believe excellent ideas have a way of becoming extraordinary products with unique customer experiences at the highest quality. When you bring passion and dedication to your job, there's no telling what you could accomplish! The people here at Apple don't just build products - they craft the kind of wonder that's revolutionized entire industries. The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help shape the future of scalable machine learning infrastructure. In this role, you'll lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple's cloud and distributed environments. You'll help define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. We are looking for an energetic and motivated individual with strong communication, organizational, and technical skills who thrives in a fast-paced, dynamic environment. We're looking for a strong Engineering Program Manager with a proven record of building and maintaining complex software platforms, tools, and processes that deliver new end-to-end experiences on-device. You will partner with teams across Apple and deliver some of the most ambitious capabilities for executing AI/ML features on scalable distributed systems, and ensuring reliability, scalability, and efficiency of ML pipelines and services. If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership,",
          "matched_input": "strong",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:04142bb145fc29907a531d701405280d:description:strong",
          "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.e2605c6bf519ddec0a",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "04142bb145fc29907a531d701405280d",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Sr Engineering Program Manager, AI/ML Cupertino, United States of America At Apple, we believe excellent ideas have a way of becoming extraordinary products with unique customer experiences at the highest quality. When you bring passion and dedication to your job, there's no telling what you could accomplish! The people here at Apple don't just build products - they craft the kind of wonder that's revolutionized entire industries. The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help shape the future of scalable machine learning infrastructure. In this role, you'll lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple's cloud and distributed environments. You'll help define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. We are looking for an energetic and motivated individual with strong communication, organizational, and technical skills who thrives in a fast-paced, dynamic environment. We're looking for a strong Engineering Program Manager with a proven record of building and maintaining complex software platforms, tools, and processes that deliver new end-to-end experiences on-device. You will partner with teams across Apple and deliver some of the most ambitious capabilities for executing AI/ML features on scalable distributed systems, and ensuring reliability, scalability, and efficiency of ML pipelines and services. If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership,",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:04142bb145fc29907a531d701405280d:description:compute",
          "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.1a1e11a4d5dcf6aed0",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "04142bb145fc29907a531d701405280d",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Sr Engineering Program Manager, AI/ML Cupertino, United States of America At Apple, we believe excellent ideas have a way of becoming extraordinary products with unique customer experiences at the highest quality. When you bring passion and dedication to your job, there's no telling what you could accomplish! The people here at Apple don't just build products - they craft the kind of wonder that's revolutionized entire industries. The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help shape the future of scalable machine learning infrastructure. In this role, you'll lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple's cloud and distributed environments. You'll help define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. We are looking for an energetic and motivated individual with strong communication, organizational, and technical skills who thrives in a fast-paced, dynamic environment. We're looking for a strong Engineering Program Manager with a proven record of building and maintaining complex software platforms, tools, and processes that deliver new end-to-end experiences on-device. You will partner with teams across Apple and deliver some of the most ambitious capabilities for executing AI/ML features on scalable distributed systems, and ensuring reliability, scalability, and efficiency of ML pipelines and services. If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership,",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.bbaedd8656760d4a79",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "04142bb145fc29907a531d701405280d",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description contains \"strong\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Sr Engineering Program Manager, AI/ML Cupertino, United States of America At Apple, we believe excellent ideas have a way of becoming extraordinary products with unique customer experiences at the highest quality. When you bring passion and dedication to your job, there's no telling what you could accomplish! The people here at Apple don't just build products - they craft the kind of wonder that's revolutionized entire industries. The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help shape the future of scalable machine learning infrastructure. In this role, you'll lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple's cloud and distributed environments. You'll help define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. We are looking for an energetic and motivated individual with strong communication, organizational, and technical skills who thrives in a fast-paced, dynamic environment. We're looking for a strong Engineering Program Manager with a proven record of building and maintaining complex software platforms, tools, and processes that deliver new end-to-end experiences on-device. You will partner with teams across Apple and deliver some of the most ambitious capabilities for executing AI/ML features on scalable distributed systems, and ensuring reliability, scalability, and efficiency of ML pipelines and services. If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership,",
          "matched_input": "strong",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200661851/sr-engineering-program-manager-ai-ml?team=SFTWR",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": null,
          "source_values": [
            "source_sector"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "11dc5e22d6d42eb034bf6a8ac34c8b49",
      "title": "Cloud Database Infrastructure Engineer",
      "employer_name": "ClickHouse",
      "employer_slug": "clickhouse",
      "location_text": "United States (Remote)",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "remote",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": 0,
      "timezone_overlap_hours": 6,
      "salary_min": 133450,
      "salary_max": 197200,
      "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": 133450,
      "base_salary_max": 197200,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "options"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cbinsights_unicorn"
      ],
      "posted_at": "2026-02-02T18:50:01.000Z",
      "apply_url": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Cloud Database Infrastructure Engineer United States (Remote) About ClickHouse Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads. The company's sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We're on a mission to transform how companies use data. Come be a part of our journey! The Cloud Scaling team is dedicated to implementing robust capabilities within the ClickHouse cloud environment. We seek exceptional software engineers to develop and maintain the infrastructure to transform ClickHouse into a fully functional serverless database solution. Collaborating closely with the core database team, we are actively working on evolving ClickHouse into a cloud-native database system. Additionally, we engage with other cloud teams to drive continuous improvements in cloud infrastructure for enhanced performance and scalability. What will you do? - Build a cutting-edge cloud-native database platform on top of the public cloud. - Work on our in-house Kubernetes operator to support seamless infrastructure management. - Improve the metrics pipeline and build systems to generate better statistics and recommendations. - Work",
      "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"
        },
        "equity_type": {
          "field": "equity_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_type"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "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"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "days_in_office": {
          "field": "days_in_office",
          "source": "rule:remote_status",
          "db_column": "days_in_office"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "growth-stage",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": 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": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.6364ecbeef4feba0c9",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "11dc5e22d6d42eb034bf6a8ac34c8b49",
          "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": "strong compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:11dc5e22d6d42eb034bf6a8ac34c8b49:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "remote_status": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "source_values": [
            "rule:remote_status"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/clickhouse/jobs/5778617004",
          "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/clickhouse/jobs/5778617004",
          "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/clickhouse/jobs/5778617004",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "06ea0d3ef053958cb6188fdb7d7afa5d",
      "title": "Strategic Projects Lead, Generative AI",
      "employer_name": "Scale AI",
      "employer_slug": "scale-ai",
      "location_text": "San Francisco, CA; New York, NY",
      "country": "US",
      "employment_type": "full_time",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 112000,
      "salary_max": 190000,
      "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": 112000,
      "base_salary_max": 190000,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "options"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cnbc_disruptor50"
      ],
      "posted_at": "2023-06-13T22:12:59.000Z",
      "apply_url": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Strategic Projects Lead, Generative AI San Francisco, CA; New York, NY Scale's Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: - Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) - Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives - Own the execution of our data labeling operations for strategic projects - Give regular progress updates to Scale's executive team - Work on some of the most impactful problems at the company Ideally, you'd have: - Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). - 2+ years of experience leading a team, developing product or operational processes, or as a SWE. - Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). - Entrepreneurial experience and mindset - you are excited about building things from scratch Compensation packages at Scale for eligible roles include base",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 47,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "employment_type": {
          "field": "employment_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "employment_type"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 2,
      "years_experience_max": 6,
      "role_function": "operations",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.03acb913893095f4b0",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "06ea0d3ef053958cb6188fdb7d7afa5d",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description matched \"strong\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Strategic Projects Lead, Generative AI San Francisco, CA; New York, NY Scale's Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: - Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) - Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives - Own the execution of our data labeling operations for strategic projects - Give regular progress updates to Scale's executive team - Work on some of the most impactful problems at the company Ideally, you'd have: - Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). - 2+ years of experience leading a team, developing product or operational processes, or as a SWE. - Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). - Entrepreneurial experience and mindset - you are excited about building things from scratch Compensation packages at Scale for eligible roles include base",
          "matched_input": "strong",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:06ea0d3ef053958cb6188fdb7d7afa5d:description:strong",
          "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.86cc7b076cebe168d8",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "06ea0d3ef053958cb6188fdb7d7afa5d",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description matched \"compute\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Strategic Projects Lead, Generative AI San Francisco, CA; New York, NY Scale's Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: - Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) - Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives - Own the execution of our data labeling operations for strategic projects - Give regular progress updates to Scale's executive team - Work on some of the most impactful problems at the company Ideally, you'd have: - Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). - 2+ years of experience leading a team, developing product or operational processes, or as a SWE. - Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). - Entrepreneurial experience and mindset - you are excited about building things from scratch Compensation packages at Scale for eligible roles include base",
          "matched_input": "compute",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_dad6f1e92322a0102143:06ea0d3ef053958cb6188fdb7d7afa5d:description:compute",
          "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.01136d0756b14fe784",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "06ea0d3ef053958cb6188fdb7d7afa5d",
          "signal_type": "query_match",
          "display_text": "Description: \"compute\"",
          "tooltip": "Description contains \"compute\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Strategic Projects Lead, Generative AI San Francisco, CA; New York, NY Scale's Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: - Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) - Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives - Own the execution of our data labeling operations for strategic projects - Give regular progress updates to Scale's executive team - Work on some of the most impactful problems at the company Ideally, you'd have: - Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). - 2+ years of experience leading a team, developing product or operational processes, or as a SWE. - Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). - Entrepreneurial experience and mindset - you are excited about building things from scratch Compensation packages at Scale for eligible roles include base",
          "matched_input": "compute",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.038bdf90e877fa227c",
          "query_id": "gq_dad6f1e92322a0102143",
          "job_id": "06ea0d3ef053958cb6188fdb7d7afa5d",
          "signal_type": "query_match",
          "display_text": "Description: \"strong\"",
          "tooltip": "Description contains \"strong\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Strategic Projects Lead, Generative AI San Francisco, CA; New York, NY Scale's Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: - Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) - Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives - Own the execution of our data labeling operations for strategic projects - Give regular progress updates to Scale's executive team - Work on some of the most impactful problems at the company Ideally, you'd have: - Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). - 2+ years of experience leading a team, developing product or operational processes, or as a SWE. - Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). - Entrepreneurial experience and mindset - you are excited about building things from scratch Compensation packages at Scale for eligible roles include base",
          "matched_input": "strong",
          "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://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_max": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/scaleai/jobs/4282118005",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    }
  ],
  "total": 3027,
  "page": 38,
  "per_page": 24,
  "applied_filters": {
    "q": "Strong Compute"
  },
  "hidden_unknown_benefits_count": 0,
  "hidden_quality_floor_count": 0,
  "quality_floor": "default",
  "search_profile": {
    "profile_id": "inv382.d6.pg_textsearch_bge_small_rrf.v1",
    "bm25_extension": "pg_textsearch",
    "vector_model": "BAAI/bge-small-en-v1.5",
    "vector_model_version": "v1.5",
    "fusion_method": "rrf"
  },
  "explanation_context": {
    "non_trivial_query": true,
    "query_terms": [
      "strong",
      "compute"
    ],
    "active_filter_keys": [],
    "visible_signal_limit": 3,
    "visible_trust_limit": 2
  },
  "event_context": {
    "query_context": {
      "query_id": "e21aa397-e193-42f9-b103-9c4d8c113567",
      "issued_at": "2026-08-27T12:44:33.883Z",
      "route": "/jobs",
      "page": 38,
      "per_page": 24,
      "total_results": 3027,
      "sort": "relevance",
      "ranking_policy": "hybrid_rrf_rerank",
      "ranking_policy_version": "inv382.jobs.search.v2",
      "query_hash": "hmac_sha256:bsy2d2XjkBmxpieTZ-3JICk4Ui4CfM9hwXrUKpPmaFY",
      "filter_hash": "hmac_sha256:6CBErDPXOFVCSNkSGbTmuw6GxoMjwSLro0KqZMtxL_0",
      "query_features": {
        "has_q": true,
        "q_term_count": 2,
        "q_length_bucket": "1_15",
        "q_pii_redacted": false,
        "state_count": 0,
        "benefit_filters": [],
        "quality_floor": "default"
      },
      "exposures": [
        {
          "result_id": "49e58ae39ff5da27235f92c94434bce6",
          "position": 889,
          "page_position": 1,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3512105345726013,
            "rrf_score": 0.00199203187250996,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 182,
            "quality_score": 45
          }
        },
        {
          "result_id": "c76137f0e8c9c6c7de367f0699dcb3b0",
          "position": 890,
          "page_position": 2,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3512589931488037,
            "rrf_score": 0.0019880715705765406,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 369,
            "quality_score": 55
          }
        },
        {
          "result_id": "9392c64e1b353afe0895616feb5a7c00",
          "position": 891,
          "page_position": 3,
          "retrieval_features": {
            "bm25_score": -5.938304424285889,
            "vector_score": 0,
            "rrf_score": 0.0019880715705765406,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 45
          }
        },
        {
          "result_id": "ca0e580089e9c47c93f6400c1349745d",
          "position": 892,
          "page_position": 4,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3512931256715569,
            "rrf_score": 0.001984126984126984,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 97,
            "quality_score": 45
          }
        },
        {
          "result_id": "08d39dcdc9fe6c89210a80e83decde14",
          "position": 893,
          "page_position": 5,
          "retrieval_features": {
            "bm25_score": -5.932514667510986,
            "vector_score": 0,
            "rrf_score": 0.001984126984126984,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 45
          }
        },
        {
          "result_id": "9a696e79d2fb342828848184b7837281",
          "position": 894,
          "page_position": 6,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35133139185122186,
            "rrf_score": 0.0019801980198019802,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 82,
            "quality_score": 35
          }
        },
        {
          "result_id": "19578d191e0a7467eba1302d0598e602",
          "position": 895,
          "page_position": 7,
          "retrieval_features": {
            "bm25_score": -5.931172847747803,
            "vector_score": 0,
            "rrf_score": 0.0019801980198019802,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 35
          }
        },
        {
          "result_id": "0e7aea57c74199e15d1104d9967553e3",
          "position": 896,
          "page_position": 8,
          "retrieval_features": {
            "bm25_score": -5.916134357452393,
            "vector_score": 0,
            "rrf_score": 0.001976284584980237,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 76,
            "quality_score": 35
          }
        },
        {
          "result_id": "228494dd0ae56816225597bde6a8d6a7",
          "position": 897,
          "page_position": 9,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35133633903644335,
            "rrf_score": 0.001976284584980237,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 227,
            "quality_score": 45
          }
        },
        {
          "result_id": "5df3a2485572eaac305b298d60609e24",
          "position": 898,
          "page_position": 10,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35139993718862794,
            "rrf_score": 0.0019723865877712033,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 89,
            "quality_score": 45
          }
        },
        {
          "result_id": "ccb2773c2ffce1adb24620d3d128dc0a",
          "position": 899,
          "page_position": 11,
          "retrieval_features": {
            "bm25_score": -5.916134357452393,
            "vector_score": 0,
            "rrf_score": 0.001968503937007874,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 35
          }
        },
        {
          "result_id": "18ba344446b6ded08eb19d351eb27ca2",
          "position": 900,
          "page_position": 12,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35140323638916016,
            "rrf_score": 0.001968503937007874,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 203,
            "quality_score": 45
          }
        },
        {
          "result_id": "b1c3ac8346445306dd7ff4f776daf08b",
          "position": 901,
          "page_position": 13,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35143691301345825,
            "rrf_score": 0.0019646365422396855,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 104,
            "quality_score": 55
          }
        },
        {
          "result_id": "a16d26a516b8889b9900536a8a895ea3",
          "position": 902,
          "page_position": 14,
          "retrieval_features": {
            "bm25_score": -5.900211811065674,
            "vector_score": 0,
            "rrf_score": 0.0019646365422396855,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 126,
            "quality_score": 55
          }
        },
        {
          "result_id": "ae5562d78b8edc7eb96a4e6577f09274",
          "position": 903,
          "page_position": 15,
          "retrieval_features": {
            "bm25_score": -5.889636516571045,
            "vector_score": 0,
            "rrf_score": 0.00196078431372549,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 596,
            "quality_score": 55
          }
        },
        {
          "result_id": "8998460b137938544a548353cdefa382",
          "position": 904,
          "page_position": 16,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35144050700181173,
            "rrf_score": 0.00196078431372549,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 92,
            "quality_score": 35
          }
        },
        {
          "result_id": "8e505696cf7036154fbfe703aac26097",
          "position": 905,
          "page_position": 17,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35144635149516656,
            "rrf_score": 0.0019569471624266144,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 107,
            "quality_score": 35
          }
        },
        {
          "result_id": "10acec96a1c5aed678eb1844c03c5823",
          "position": 906,
          "page_position": 18,
          "retrieval_features": {
            "bm25_score": -5.886285305023193,
            "vector_score": 0,
            "rrf_score": 0.0019569471624266144,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 35
          }
        },
        {
          "result_id": "2b661a8edc7fbfadd27856b02b7e5d4c",
          "position": 907,
          "page_position": 19,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3514554500579834,
            "rrf_score": 0.001953125,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 125,
            "quality_score": 55
          }
        },
        {
          "result_id": "5b689a0e55e21c1c6ea372923623c584",
          "position": 908,
          "page_position": 20,
          "retrieval_features": {
            "bm25_score": -5.886285305023193,
            "vector_score": 0,
            "rrf_score": 0.001953125,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 35
          }
        },
        {
          "result_id": "25ce0faaa45f3edd87b486324f26b728",
          "position": 909,
          "page_position": 21,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35145998001098633,
            "rrf_score": 0.001949317738791423,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 85,
            "quality_score": 45
          }
        },
        {
          "result_id": "04142bb145fc29907a531d701405280d",
          "position": 910,
          "page_position": 22,
          "retrieval_features": {
            "bm25_score": -5.84600043296814,
            "vector_score": 0,
            "rrf_score": 0.0019455252918287938,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 112,
            "quality_score": 55
          }
        },
        {
          "result_id": "11dc5e22d6d42eb034bf6a8ac34c8b49",
          "position": 911,
          "page_position": 23,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.35146484664291944,
            "rrf_score": 0.0019455252918287938,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 205,
            "quality_score": 55
          }
        },
        {
          "result_id": "06ea0d3ef053958cb6188fdb7d7afa5d",
          "position": 912,
          "page_position": 24,
          "retrieval_features": {
            "bm25_score": -5.84600043296814,
            "vector_score": 0,
            "rrf_score": 0.001941747572815534,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 1170,
            "quality_score": 55
          }
        }
      ]
    },
    "context_signature": "AVyzUMQjsVWi7IOcC1JZox1OLtqCGGCqm-jqWrdVme4",
    "event_token": "AVyzUMQjsVWi7IOcC1JZox1OLtqCGGCqm-jqWrdVme4"
  }
}