{
  "results": [
    {
      "id": "bc30f92bf8a07da236ca7e6c1835d8e5",
      "title": "Research Engineer, Robotics",
      "employer_name": "Meta",
      "employer_slug": "meta",
      "location_text": "Redmond, WA",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 219000,
      "salary_max": 301000,
      "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": 219000,
      "base_salary_max": 301000,
      "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": 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://www.metacareers.com/jobs/1331776965685553/",
      "apply_url_verified": false,
      "ats": "meta_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Research Engineer, Robotics Redmond, WA Reality Labs Research (Reality Labs Research) brings together a multidisciplinary and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic manipulation. We are seeking a senior staff Research Engineer to design and build a custom CUDA-based compute renderer for robotics. You will own this end-to-end - architecting and implementing a novel GPU rendering system that serves as the visual backbone for robot learning at scale. This is a deeply technical, hands-on IC role for someone who has built rendering systems before. Responsibilities: - Design and implement a custom compute renderer: Build a CUDA compute renderer supporting rasterization and ray tracing, optimized for high-throughput batch rendering on datacenter GPUs - Write high-performance GPU kernels: Develop and optimize kernels for core rendering operations including geometry processing, shading, light transport, and image synthesis - Produce ML-ready rendering outputs: Generate rendering outputs (RGB, depth, segmentation) suitable for direct consumption by ML training pipelines - Integrate into policy and training pipelines: Embed rendering capabilities into policy training loops, evaluation harnesses, and dataset generation workflows enabling end-to-end visual learning for robotic manipulation - Integrate with physics simulation: Render dynamic scenes including articulated rigid bodies, deformable objects, and skinned meshes in coordination with physics simulation systems - Collaborate on speed/quality tradeoffs: Partner closely with Research Scientists and ML Engineers to understand requirements and make principled tradeoffs between rendering fidelity and throughput - Own the full rendering stack: Maintain end-to-end ownership from scene ingestion through final image output,",
      "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": "2026-06-07T00:00:00Z",
      "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": "salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1326801/000162828026003942/meta-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/1326801/000162828026003942/meta-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 10,
      "years_experience_max": 14,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "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": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.894248ece079bde5a7",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "bc30f92bf8a07da236ca7e6c1835d8e5",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Research Engineer, Robotics Redmond, WA Reality Labs Research (Reality Labs Research) brings together a multidisciplinary and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic manipulation. We are seeking a senior staff Research Engineer to design and build a custom CUDA-based compute renderer for robotics. You will own this end-to-end - architecting and implementing a novel GPU rendering system that serves as the visual backbone for robot learning at scale. This is a deeply technical, hands-on IC role for someone who has built rendering systems before. Responsibilities: - Design and implement a custom compute renderer: Build a CUDA compute renderer supporting rasterization and ray tracing, optimized for high-throughput batch rendering on datacenter GPUs - Write high-performance GPU kernels: Develop and optimize kernels for core rendering operations including geometry processing, shading, light transport, and image synthesis - Produce ML-ready rendering outputs: Generate rendering outputs (RGB, depth, segmentation) suitable for direct consumption by ML training pipelines - Integrate into policy and training pipelines: Embed rendering capabilities into policy training loops, evaluation harnesses, and dataset generation workflows enabling end-to-end visual learning for robotic manipulation - Integrate with physics simulation: Render dynamic scenes including articulated rigid bodies, deformable objects, and skinned meshes in coordination with physics simulation systems - Collaborate on speed/quality tradeoffs: Partner closely with Research Scientists and ML Engineers to understand requirements and make principled tradeoffs between rendering fidelity and throughput - Own the full rendering stack: Maintain end-to-end ownership from scene ingestion through final image output,",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:bc30f92bf8a07da236ca7e6c1835d8e5:description:kernel",
          "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.29e463762ffa99b3f1",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "bc30f92bf8a07da236ca7e6c1835d8e5",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Research Engineer, Robotics Redmond, WA Reality Labs Research (Reality Labs Research) brings together a multidisciplinary and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic manipulation. We are seeking a senior staff Research Engineer to design and build a custom CUDA-based compute renderer for robotics. You will own this end-to-end - architecting and implementing a novel GPU rendering system that serves as the visual backbone for robot learning at scale. This is a deeply technical, hands-on IC role for someone who has built rendering systems before. Responsibilities: - Design and implement a custom compute renderer: Build a CUDA compute renderer supporting rasterization and ray tracing, optimized for high-throughput batch rendering on datacenter GPUs - Write high-performance GPU kernels: Develop and optimize kernels for core rendering operations including geometry processing, shading, light transport, and image synthesis - Produce ML-ready rendering outputs: Generate rendering outputs (RGB, depth, segmentation) suitable for direct consumption by ML training pipelines - Integrate into policy and training pipelines: Embed rendering capabilities into policy training loops, evaluation harnesses, and dataset generation workflows enabling end-to-end visual learning for robotic manipulation - Integrate with physics simulation: Render dynamic scenes including articulated rigid bodies, deformable objects, and skinned meshes in coordination with physics simulation systems - Collaborate on speed/quality tradeoffs: Partner closely with Research Scientists and ML Engineers to understand requirements and make principled tradeoffs between rendering fidelity and throughput - Own the full rendering stack: Maintain end-to-end ownership from scene ingestion through final image output,",
          "matched_input": "kernel",
          "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://www.metacareers.com/jobs/1331776965685553/",
          "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.metacareers.com/jobs/1331776965685553/",
          "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.metacareers.com/jobs/1331776965685553/",
          "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/1326801/000162828026003942/meta-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1326801/000162828026003942/meta-20251231.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": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://www.metacareers.com/jobs/1331776965685553/",
          "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.metacareers.com/jobs/1331776965685553/",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "011bde266387b45b3977c297b51573dd",
      "title": "Machine Learning Engineer",
      "employer_name": "Autodesk",
      "employer_slug": "autodesk",
      "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": "2026-05-12T00:00:00.000Z",
      "apply_url": "https://autodesk.wd1.myworkdayjobs.com/Ext/job/EMEA---Serbia---Novi-Sad---Zeleznicka-7/ML-Engineer_25WD93759",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Machine Learning Engineer 2 Locations posted: Posted 30+ Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "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/769397/000076939726000015/adsk-20260131.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/769397/000076939726000015/adsk-20260131.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.1e65e66171dba6a135",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "011bde266387b45b3977c297b51573dd",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:011bde266387b45b3977c297b51573dd: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/769397/000076939726000015/adsk-20260131.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/769397/000076939726000015/adsk-20260131.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://autodesk.wd1.myworkdayjobs.com/Ext/job/EMEA---Serbia---Novi-Sad---Zeleznicka-7/ML-Engineer_25WD93759",
          "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://autodesk.wd1.myworkdayjobs.com/Ext/job/EMEA---Serbia---Novi-Sad---Zeleznicka-7/ML-Engineer_25WD93759",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "c53738d5934d42e8ec71a07ea0191faf",
      "title": "Test Engineer/OS Certification Engineer",
      "employer_name": "Supermicro",
      "employer_slug": "supermicro",
      "location_text": "US - HQ (US001) | Country United States | State California | City San Jose",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options"
      ],
      "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://jobs.supermicro.com/job/San-Jose-Test-EngineerOS-Certification-Engineer-Cali/1398215400/",
      "apply_url_verified": false,
      "ats": "successfactors",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Test Engineer/OS Certification Engineer US - HQ (US001) | Country United States | State California | City San Jose Job Req ID: 29121 About Supermicro: Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide. We are the #5 fastest growing company among the Silicon Valley Top 50 technology firms. Our unprecedented global expansion has provided us with the opportunity to offer a large number of new positions to the technology community. We seek talented, passionate, and committed engineers, technologists, and business leaders to join us. Job Summary: We are looking for an OS Certification Engineer to execute operating system certification, compatibility testing, and compliance validation across enterprise server platforms and hardware components. Essential Duties and Responsibilities: Key Responsibilities: OS Certification Execution: Run official Linux certification test suites (e.g., Red Hat Enterprise Linux, Ubuntu certification) on server platforms. Platform Validation: Assist in validating system images, drivers, kernel patches, and firmware (BIOS/UEFI/BMC) for hardware interoperability. Network & Driver Validation: Test server-level networking stacks, interface cards, and protocol compatibility (TCP/IP, DHCP, PXE boot). Debugging & Log Analysis: Review system and kernel logs to identify certification failures, and coordinate findings with hardware and BIOS engineering teams. Automation Support: Use and maintain automated test scripts to",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1375365/000137536525000027/smci-20250630.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1375365/000137536525000027/smci-20250630.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": "Technology",
      "employer_industry_source": "wikidata_sparql_industry",
      "employer_size": "5000+",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.d837a0c8dea7385fa1",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "c53738d5934d42e8ec71a07ea0191faf",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Test Engineer/OS Certification Engineer US - HQ (US001) | Country United States | State California | City San Jose Job Req ID: 29121 About Supermicro: Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide. We are the #5 fastest growing company among the Silicon Valley Top 50 technology firms. Our unprecedented global expansion has provided us with the opportunity to offer a large number of new positions to the technology community. We seek talented, passionate, and committed engineers, technologists, and business leaders to join us. Job Summary: We are looking for an OS Certification Engineer to execute operating system certification, compatibility testing, and compliance validation across enterprise server platforms and hardware components. Essential Duties and Responsibilities: Key Responsibilities: OS Certification Execution: Run official Linux certification test suites (e.g., Red Hat Enterprise Linux, Ubuntu certification) on server platforms. Platform Validation: Assist in validating system images, drivers, kernel patches, and firmware (BIOS/UEFI/BMC) for hardware interoperability. Network & Driver Validation: Test server-level networking stacks, interface cards, and protocol compatibility (TCP/IP, DHCP, PXE boot). Debugging & Log Analysis: Review system and kernel logs to identify certification failures, and coordinate findings with hardware and BIOS engineering teams. Automation Support: Use and maintain automated test scripts to",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:c53738d5934d42e8ec71a07ea0191faf:description:kernel",
          "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.4eb597b5b92ffa729b",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "c53738d5934d42e8ec71a07ea0191faf",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Test Engineer/OS Certification Engineer US - HQ (US001) | Country United States | State California | City San Jose Job Req ID: 29121 About Supermicro: Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide. We are the #5 fastest growing company among the Silicon Valley Top 50 technology firms. Our unprecedented global expansion has provided us with the opportunity to offer a large number of new positions to the technology community. We seek talented, passionate, and committed engineers, technologists, and business leaders to join us. Job Summary: We are looking for an OS Certification Engineer to execute operating system certification, compatibility testing, and compliance validation across enterprise server platforms and hardware components. Essential Duties and Responsibilities: Key Responsibilities: OS Certification Execution: Run official Linux certification test suites (e.g., Red Hat Enterprise Linux, Ubuntu certification) on server platforms. Platform Validation: Assist in validating system images, drivers, kernel patches, and firmware (BIOS/UEFI/BMC) for hardware interoperability. Network & Driver Validation: Test server-level networking stacks, interface cards, and protocol compatibility (TCP/IP, DHCP, PXE boot). Debugging & Log Analysis: Review system and kernel logs to identify certification failures, and coordinate findings with hardware and BIOS engineering teams. Automation Support: Use and maintain automated test scripts to",
          "matched_input": "kernel",
          "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/1375365/000137536525000027/smci-20250630.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1375365/000137536525000027/smci-20250630.htm"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.supermicro.com/job/San-Jose-Test-EngineerOS-Certification-Engineer-Cali/1398215400/",
          "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.supermicro.com/job/San-Jose-Test-EngineerOS-Certification-Engineer-Cali/1398215400/",
          "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.supermicro.com/job/San-Jose-Test-EngineerOS-Certification-Engineer-Cali/1398215400/",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - Wikidata",
          "source_label": "Wikidata",
          "href": null,
          "source_values": [
            "wikidata_sparql_industry"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "6a5aaa9345090f83df9983da6e47db1d",
      "title": "Principal Applied Research Scientist (Datagrid)",
      "employer_name": "Procore",
      "employer_slug": "procore",
      "location_text": "US - California - Bay Area",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": 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": "2026-06-09T00:00:00.000Z",
      "apply_url": "https://procore.wd12.myworkdayjobs.com/Procore_External_Careers/job/US---California---Bay-Area/Principal-Applied-Research-Scientist--Datagrid-_R0017693",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Principal Applied Research Scientist (Datagrid) US - California - Bay Area posted: Posted 3 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": 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/1611052/000162828026011055/pcor-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1611052/000162828026011055/pcor-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 8,
      "years_experience_max": 12,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.8eed01a0fdf57f4b59",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "6a5aaa9345090f83df9983da6e47db1d",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:6a5aaa9345090f83df9983da6e47db1d:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1611052/000162828026011055/pcor-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1611052/000162828026011055/pcor-20251231.htm"
          ],
          "checked_at": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://procore.wd12.myworkdayjobs.com/Procore_External_Careers/job/US---California---Bay-Area/Principal-Applied-Research-Scientist--Datagrid-_R0017693",
          "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://procore.wd12.myworkdayjobs.com/Procore_External_Careers/job/US---California---Bay-Area/Principal-Applied-Research-Scientist--Datagrid-_R0017693",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "cc5495b1444e1136cae6fa38e90e033e",
      "title": "Junior or Software Engineer - Red Hat Linux Virtualization (Brno Office, Czech Republic)",
      "employer_name": "Neural Magic",
      "employer_slug": "neural-magic",
      "location_text": "Brno - Tech Park Brno - C",
      "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": [
        "a16z"
      ],
      "posted_at": "2026-05-25T00:00:00.000Z",
      "apply_url": "https://redhat.wd5.myworkdayjobs.com/jobs/job/Brno---Tech-Park-Brno---C/Junior-or-Software-Engineer---Red-Hat-Linux-Virtualization--Brno-Office--Czech-Republic-_R-056276-1",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Junior or Software Engineer - Red Hat Linux Virtualization (Brno Office, Czech Republic) Brno - Tech Park Brno - C posted: Posted 18 Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 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:title_override",
          "db_column": "role_function"
        },
        "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": "engineering",
      "role_function_source": "rule:title_override",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 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.ba65f3c3ca5569ce6a",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "cc5495b1444e1136cae6fa38e90e033e",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:cc5495b1444e1136cae6fa38e90e033e:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": null
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://redhat.wd5.myworkdayjobs.com/jobs/job/Brno---Tech-Park-Brno---C/Junior-or-Software-Engineer---Red-Hat-Linux-Virtualization--Brno-Office--Czech-Republic-_R-056276-1",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://redhat.wd5.myworkdayjobs.com/jobs/job/Brno---Tech-Park-Brno---C/Junior-or-Software-Engineer---Red-Hat-Linux-Virtualization--Brno-Office--Czech-Republic-_R-056276-1",
          "source_values": [
            "rule:title_override"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "cc18e70019c232c706fb0b8570ae823b",
      "title": "Staff Technical Lead for Inference & ML Performance",
      "employer_name": "Fal",
      "employer_slug": "fal",
      "location_text": "San Francisco",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": 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",
        "a16z",
        "sequoia"
      ],
      "posted_at": "2025-08-07T15:45:09.000Z",
      "apply_url": "https://job-boards.greenhouse.io/fal/jobs/4012780009",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Staff Technical Lead for Inference & ML Performance San Francisco fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. Why this role matters You'll shape the future of fal's inference engine and ensure our generative models achieve best-in-class performance. Your work directly impacts our ability to rapidly deliver cutting-edge creative solutions to users, from individual creators to global brands. What you'll do Day-to-day What success looks like Set technical direction. Guide your team (kernels, applied performance, ML compilers, distributed inference) to build high-performance inference solutions. fal's inference engine consistently outperforms industry benchmarks in throughput, latency, and efficiency. Hands-on IC leadership. Personally contribute to critical inference performance enhancements and optimizations. You regularly ship code that significantly improves model serving performance. Collaborate closely with research & applied ML teams. Influence model inference strategies and deployment techniques. Seamless integration of inference innovations rapidly moves from research to production deployment. Drive advanced performance optimizations. Implement model parallelism, kernel optimization, and compiler strategies.",
      "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"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "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": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.fb110cf94e75e74972",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "cc18e70019c232c706fb0b8570ae823b",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Staff Technical Lead for Inference & ML Performance San Francisco fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. Why this role matters You'll shape the future of fal's inference engine and ensure our generative models achieve best-in-class performance. Your work directly impacts our ability to rapidly deliver cutting-edge creative solutions to users, from individual creators to global brands. What you'll do Day-to-day What success looks like Set technical direction. Guide your team (kernels, applied performance, ML compilers, distributed inference) to build high-performance inference solutions. fal's inference engine consistently outperforms industry benchmarks in throughput, latency, and efficiency. Hands-on IC leadership. Personally contribute to critical inference performance enhancements and optimizations. You regularly ship code that significantly improves model serving performance. Collaborate closely with research & applied ML teams. Influence model inference strategies and deployment techniques. Seamless integration of inference innovations rapidly moves from research to production deployment. Drive advanced performance optimizations. Implement model parallelism, kernel optimization, and compiler strategies.",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:cc18e70019c232c706fb0b8570ae823b:description:kernel",
          "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.722c038df05f2e63c7",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "cc18e70019c232c706fb0b8570ae823b",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Staff Technical Lead for Inference & ML Performance San Francisco fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. Why this role matters You'll shape the future of fal's inference engine and ensure our generative models achieve best-in-class performance. Your work directly impacts our ability to rapidly deliver cutting-edge creative solutions to users, from individual creators to global brands. What you'll do Day-to-day What success looks like Set technical direction. Guide your team (kernels, applied performance, ML compilers, distributed inference) to build high-performance inference solutions. fal's inference engine consistently outperforms industry benchmarks in throughput, latency, and efficiency. Hands-on IC leadership. Personally contribute to critical inference performance enhancements and optimizations. You regularly ship code that significantly improves model serving performance. Collaborate closely with research & applied ML teams. Influence model inference strategies and deployment techniques. Seamless integration of inference innovations rapidly moves from research to production deployment. Drive advanced performance optimizations. Implement model parallelism, kernel optimization, and compiler strategies.",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/fal/jobs/4012780009",
          "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/fal/jobs/4012780009",
          "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/fal/jobs/4012780009",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "0930c2382c4b1757258c46c18e9354e0",
      "title": "2026 University Graduate - Machine Learning Engineer",
      "employer_name": "Adobe Inc.",
      "employer_slug": "adobe",
      "location_text": "Seattle",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-12T00:00:00.000Z",
      "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Seattle/XMLNAME-2026-University-Graduate---Machine-Learning-Engineer_R160133",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "2026 University Graduate - Machine Learning Engineer Seattle posted: Posted 30+ Days Ago",
      "parental_leave_weeks": 16,
      "non_birth_parent_leave_weeks": 16,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 90,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "parental_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.474a808b5f4edc4ae2",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "0930c2382c4b1757258c46c18e9354e0",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:0930c2382c4b1757258c46c18e9354e0:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm"
          ],
          "checked_at": null
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Seattle/XMLNAME-2026-University-Graduate---Machine-Learning-Engineer_R160133",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Seattle/XMLNAME-2026-University-Graduate---Machine-Learning-Engineer_R160133",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-05-07"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Seattle/XMLNAME-2026-University-Graduate---Machine-Learning-Engineer_R160133",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Seattle/XMLNAME-2026-University-Graduate---Machine-Learning-Engineer_R160133",
          "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": "d20253b11766adc2e0295ab1ba885e90",
      "title": "Embedded Linux Software Engineer",
      "employer_name": "Sunday",
      "employer_slug": "sunday",
      "location_text": "Redwood City, CA, Redwood City, California, United States",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cbinsights_unicorn",
        "sequoia"
      ],
      "posted_at": "2026-04-27T18:16:42.398Z",
      "apply_url": "https://jobs.ashbyhq.com/sunday/788d2c63-f5b7-447e-9d4d-7ab1a92e10f1",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Embedded Linux Software Engineer Redwood City, CA, Redwood City, California, United States Join Us in Building the Future of Home Robotics At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time. We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you. What to Expect As an Embedded Linux Software Engineer, you'll own platform software for the embedded Linux compute units running our robotics stack. You will collaborate closely with electrical, mechanical, software, and machine-learning teams to integrate our full robotics stack on a new compute. What You'll Do - Own the embedded software stack (bootloader, kernel, devicetree, BSP, and drivers) for compute platforms based on SoCs like NVIDIA Jetson, Qualcomm etc - Develop and maintain Linux kernel drivers and userspace integration for sensors, GMSL cameras, displays, storage, and high-speed interconnects (PCIe, USB, MIPI CSI/DSI, Ethernet, CAN) - Own build system and BSP layers using Yocto/Buildroot or vendor SDKs like JetPack - Work with the electrical engineering team to debug and bring up custom carrier boards - Work closely with the software and machine-learning teams to optimize performance across the entire software stack - Design",
      "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": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.a8453b0975bf5f21e0",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "d20253b11766adc2e0295ab1ba885e90",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Embedded Linux Software Engineer Redwood City, CA, Redwood City, California, United States Join Us in Building the Future of Home Robotics At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time. We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you. What to Expect As an Embedded Linux Software Engineer, you'll own platform software for the embedded Linux compute units running our robotics stack. You will collaborate closely with electrical, mechanical, software, and machine-learning teams to integrate our full robotics stack on a new compute. What You'll Do - Own the embedded software stack (bootloader, kernel, devicetree, BSP, and drivers) for compute platforms based on SoCs like NVIDIA Jetson, Qualcomm etc - Develop and maintain Linux kernel drivers and userspace integration for sensors, GMSL cameras, displays, storage, and high-speed interconnects (PCIe, USB, MIPI CSI/DSI, Ethernet, CAN) - Own build system and BSP layers using Yocto/Buildroot or vendor SDKs like JetPack - Work with the electrical engineering team to debug and bring up custom carrier boards - Work closely with the software and machine-learning teams to optimize performance across the entire software stack - Design",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:d20253b11766adc2e0295ab1ba885e90:description:kernel",
          "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.e1f5077827904e82f4",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "d20253b11766adc2e0295ab1ba885e90",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Embedded Linux Software Engineer Redwood City, CA, Redwood City, California, United States Join Us in Building the Future of Home Robotics At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time. We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you. What to Expect As an Embedded Linux Software Engineer, you'll own platform software for the embedded Linux compute units running our robotics stack. You will collaborate closely with electrical, mechanical, software, and machine-learning teams to integrate our full robotics stack on a new compute. What You'll Do - Own the embedded software stack (bootloader, kernel, devicetree, BSP, and drivers) for compute platforms based on SoCs like NVIDIA Jetson, Qualcomm etc - Develop and maintain Linux kernel drivers and userspace integration for sensors, GMSL cameras, displays, storage, and high-speed interconnects (PCIe, USB, MIPI CSI/DSI, Ethernet, CAN) - Own build system and BSP layers using Yocto/Buildroot or vendor SDKs like JetPack - Work with the electrical engineering team to debug and bring up custom carrier boards - Work closely with the software and machine-learning teams to optimize performance across the entire software stack - Design",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/sunday/788d2c63-f5b7-447e-9d4d-7ab1a92e10f1",
          "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/sunday/788d2c63-f5b7-447e-9d4d-7ab1a92e10f1",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "b5cf3c2a57a7a1db0bbd0a71a9456eb7",
      "title": "Senior Linux Firmware Engineer",
      "employer_name": "Eaton Corporation",
      "employer_slug": "eaton",
      "location_text": "Raleigh, North Carolina, USA, 27616",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-06-12T10:25:24.000Z",
      "apply_url": "https://eaton.eightfold.ai/careers/job/687236844580",
      "apply_url_verified": false,
      "ats": "eightfold",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior Linux Firmware Engineer Raleigh, North Carolina, USA, 27616",
      "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/1551182/000155118226000007/etn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1551182/000155118226000007/etn-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.dd4e255facc9c9d985",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "b5cf3c2a57a7a1db0bbd0a71a9456eb7",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:b5cf3c2a57a7a1db0bbd0a71a9456eb7: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/1551182/000155118226000007/etn-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1551182/000155118226000007/etn-20251231.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://eaton.eightfold.ai/careers/job/687236844580",
          "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://eaton.eightfold.ai/careers/job/687236844580",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "d5e13144b34f3d7ebc6c4944cf57f844",
      "title": "Software Engineer, Inference – AMD GPU Enablement",
      "employer_name": "OpenAI",
      "employer_slug": "openai",
      "location_text": "San Francisco, California, United States",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "cnbc_disruptor50",
        "cbinsights_unicorn",
        "a16z",
        "sequoia",
        "foundersfund"
      ],
      "posted_at": "2025-10-08T20:51:30.392Z",
      "apply_url": "https://jobs.ashbyhq.com/openai/9b79406c-89a8-49bd-8a38-e72db80996e9",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Software Engineer, Inference – AMD GPU Enablement San Francisco, California, United States About the Team Our Inference team brings OpenAI's most capable research and technology to the world through our products. We empower consumers, enterprises and developers alike to use and access our state-of-the-art AI models, allowing them to do things that they've never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We're hiring engineers to scale and optimize OpenAI's inference infrastructure across emerging GPU platforms. You'll work across the stack - from low-level kernel performance to high-level distributed execution - and collaborate closely with research, infra, and performance teams to ensure our largest models run smoothly on new hardware. This is a high-impact opportunity to shape OpenAI's multi-platform inference capabilities from the ground up with a particular focus on advancing inference performance on AMD accelerators. In this role, you will: - Own bring-up, correctness and performance of the OpenAI inference stack on AMD hardware. - Integrate internal model-serving infrastructure (e.g., vLLM, Triton) into a variety of GPU-backed systems. - Debug and optimize distributed inference workloads across memory, network, and compute layers. - Validate correctness, performance, and scalability of model execution on large GPU clusters. - Collaborate with partner teams to design and optimize high-performance GPU kernels for accelerators using HIP, Triton, or other performance-focused frameworks. - Collaborate with partner teams to build, integrate and tune collective communication libraries (e.g., RCCL) used to parallelize",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.840cb0491105a55213",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "d5e13144b34f3d7ebc6c4944cf57f844",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Software Engineer, Inference – AMD GPU Enablement San Francisco, California, United States About the Team Our Inference team brings OpenAI's most capable research and technology to the world through our products. We empower consumers, enterprises and developers alike to use and access our state-of-the-art AI models, allowing them to do things that they've never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We're hiring engineers to scale and optimize OpenAI's inference infrastructure across emerging GPU platforms. You'll work across the stack - from low-level kernel performance to high-level distributed execution - and collaborate closely with research, infra, and performance teams to ensure our largest models run smoothly on new hardware. This is a high-impact opportunity to shape OpenAI's multi-platform inference capabilities from the ground up with a particular focus on advancing inference performance on AMD accelerators. In this role, you will: - Own bring-up, correctness and performance of the OpenAI inference stack on AMD hardware. - Integrate internal model-serving infrastructure (e.g., vLLM, Triton) into a variety of GPU-backed systems. - Debug and optimize distributed inference workloads across memory, network, and compute layers. - Validate correctness, performance, and scalability of model execution on large GPU clusters. - Collaborate with partner teams to design and optimize high-performance GPU kernels for accelerators using HIP, Triton, or other performance-focused frameworks. - Collaborate with partner teams to build, integrate and tune collective communication libraries (e.g., RCCL) used to parallelize",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:d5e13144b34f3d7ebc6c4944cf57f844:description:kernel",
          "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.7337cfdd82491a62c9",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "d5e13144b34f3d7ebc6c4944cf57f844",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Software Engineer, Inference – AMD GPU Enablement San Francisco, California, United States About the Team Our Inference team brings OpenAI's most capable research and technology to the world through our products. We empower consumers, enterprises and developers alike to use and access our state-of-the-art AI models, allowing them to do things that they've never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We're hiring engineers to scale and optimize OpenAI's inference infrastructure across emerging GPU platforms. You'll work across the stack - from low-level kernel performance to high-level distributed execution - and collaborate closely with research, infra, and performance teams to ensure our largest models run smoothly on new hardware. This is a high-impact opportunity to shape OpenAI's multi-platform inference capabilities from the ground up with a particular focus on advancing inference performance on AMD accelerators. In this role, you will: - Own bring-up, correctness and performance of the OpenAI inference stack on AMD hardware. - Integrate internal model-serving infrastructure (e.g., vLLM, Triton) into a variety of GPU-backed systems. - Debug and optimize distributed inference workloads across memory, network, and compute layers. - Validate correctness, performance, and scalability of model execution on large GPU clusters. - Collaborate with partner teams to design and optimize high-performance GPU kernels for accelerators using HIP, Triton, or other performance-focused frameworks. - Collaborate with partner teams to build, integrate and tune collective communication libraries (e.g., RCCL) used to parallelize",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/openai/9b79406c-89a8-49bd-8a38-e72db80996e9",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/openai/9b79406c-89a8-49bd-8a38-e72db80996e9",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "151aa64c6a8a830ad60e40c1571f94e7",
      "title": "Linux Engineer, VP",
      "employer_name": "Mitsubishi UFJ Financial Group,Inc.",
      "employer_slug": "mitsubishi-ufj-financial-group",
      "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": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-20T00:00:00.000Z",
      "apply_url": "https://mufgub.wd3.myworkdayjobs.com/MUFG-Careers/job/Jersey-City-NJ/Linux-Engineer_10076479-WD",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Linux Engineer, VP 2 Locations posted: Posted 23 Days Ago",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 8,
      "years_experience_max": 12,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Finance",
      "employer_industry_source": "source_sector",
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.d57acd185e2e33bdb2",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "151aa64c6a8a830ad60e40c1571f94e7",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:151aa64c6a8a830ad60e40c1571f94e7:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://mufgub.wd3.myworkdayjobs.com/MUFG-Careers/job/Jersey-City-NJ/Linux-Engineer_10076479-WD",
          "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://mufgub.wd3.myworkdayjobs.com/MUFG-Careers/job/Jersey-City-NJ/Linux-Engineer_10076479-WD",
          "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": "5f146c2f6b0de6c68e4e963394296661",
      "title": "Principal Machine Learning Engineer",
      "employer_name": "Workday, Inc.",
      "employer_slug": "workday",
      "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",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-06-05T00:00:00.000Z",
      "apply_url": "https://workday.wd5.myworkdayjobs.com/Workday/job/USA-WA-Seattle/Principal-Machine-Learning-Engineer_JR-0107128",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Principal Machine Learning Engineer 3 Locations posted: Posted 7 Days Ago",
      "parental_leave_weeks": 12,
      "non_birth_parent_leave_weeks": 12,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 89,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1327811/000132781126000014/wday-20260131.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1327811/000132781126000014/wday-20260131.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence",
          "db_column": "parental_leave_weeks",
          "source_url": "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 8,
      "years_experience_max": 12,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "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.d8002256461c6189da",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "5f146c2f6b0de6c68e4e963394296661",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:5f146c2f6b0de6c68e4e963394296661:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1327811/000132781126000014/wday-20260131.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1327811/000132781126000014/wday-20260131.htm"
          ],
          "checked_at": null
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://workday.wd5.myworkdayjobs.com/Workday/job/USA-WA-Seattle/Principal-Machine-Learning-Engineer_JR-0107128",
          "source_values": [
            "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://workday.wd5.myworkdayjobs.com/Workday/job/USA-WA-Seattle/Principal-Machine-Learning-Engineer_JR-0107128",
          "source_values": [
            "https://workdaybenefits.com/us/social-and-flex/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-05-07"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://workday.wd5.myworkdayjobs.com/Workday/job/USA-WA-Seattle/Principal-Machine-Learning-Engineer_JR-0107128",
          "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://workday.wd5.myworkdayjobs.com/Workday/job/USA-WA-Seattle/Principal-Machine-Learning-Engineer_JR-0107128",
          "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": "e7d702a9a9c389721beecee5c80e5068",
      "title": "Distributed Systems Engineer — Full Time",
      "employer_name": "Dedalus Labs",
      "employer_slug": "dedalus-labs",
      "location_text": "Main Office | OnSite",
      "country": "unknown",
      "employment_type": "full_time",
      "remote_status": "onsite",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": 5,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [
        "yc"
      ],
      "posted_at": "2026-06-10T03:52:15.000Z",
      "apply_url": "https://jobs.ashbyhq.com/dedalus-labs/e71ec106-a376-42cb-88de-264c95d423ed",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Distributed Systems Engineer — Full Time Main Office | OnSite Dedalus (YC S25) is hiring a full-time distributed systems engineer to help build the infrastructure layer powering the next generation of AI agents. We are building persistent compute infrastructure, cloud sandboxes, and developer tools for long-running AI agents. Our systems span virtualization, orchestration, storage, networking, and low-level runtime infrastructure. The role is based in San Francisco and involves working closely with a small, highly technical team operating at startup speed. WHAT YOU'LL WORK ON - Distributed systems infrastructure for large-scale agent workloads - Virtualization and sandboxing technologies - Persistent compute and storage systems - Scheduling, orchestration, and reliability engineering - Performance optimization across systems layers - Internal developer platforms and infrastructure tooling - Production systems operating under real-world scale and latency constraints REQUIREMENTS - Strong systems programming ability in Rust (preferred), Go, C/C++, or similar languages - Graduate-level knowledge of distributed systems and operating systems concepts - Experience building distributed systems in industry, research, or open source - Experience with Kubernetes and modern cloud infrastructure - Familiarity with one or more of the following: - distributed block storage - consistency models - virtualization and hypervisors - kernel or low-level systems architecture - Strong understanding of systems performance, reliability, and debugging NICE-TO-HAVE - Published systems research papers (NSDI, OSDI, SOSP, ATC, EuroSys, etc.) - Experience working on operating systems, kernels, or virtualization stacks - Contributions to open-source systems projects (Linux, Firecracker, Cloud Hypervisor, etc.) - Experience with low-level performance optimizatio",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "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"
        },
        "employment_type": {
          "field": "employment_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "employment_type"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "early",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.5aef32c871ce369a83",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "e7d702a9a9c389721beecee5c80e5068",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Distributed Systems Engineer — Full Time Main Office | OnSite Dedalus (YC S25) is hiring a full-time distributed systems engineer to help build the infrastructure layer powering the next generation of AI agents. We are building persistent compute infrastructure, cloud sandboxes, and developer tools for long-running AI agents. Our systems span virtualization, orchestration, storage, networking, and low-level runtime infrastructure. The role is based in San Francisco and involves working closely with a small, highly technical team operating at startup speed. WHAT YOU'LL WORK ON - Distributed systems infrastructure for large-scale agent workloads - Virtualization and sandboxing technologies - Persistent compute and storage systems - Scheduling, orchestration, and reliability engineering - Performance optimization across systems layers - Internal developer platforms and infrastructure tooling - Production systems operating under real-world scale and latency constraints REQUIREMENTS - Strong systems programming ability in Rust (preferred), Go, C/C++, or similar languages - Graduate-level knowledge of distributed systems and operating systems concepts - Experience building distributed systems in industry, research, or open source - Experience with Kubernetes and modern cloud infrastructure - Familiarity with one or more of the following: - distributed block storage - consistency models - virtualization and hypervisors - kernel or low-level systems architecture - Strong understanding of systems performance, reliability, and debugging NICE-TO-HAVE - Published systems research papers (NSDI, OSDI, SOSP, ATC, EuroSys, etc.) - Experience working on operating systems, kernels, or virtualization stacks - Contributions to open-source systems projects (Linux, Firecracker, Cloud Hypervisor, etc.) - Experience with low-level performance optimizatio",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:e7d702a9a9c389721beecee5c80e5068:description:kernel",
          "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.db3bdf37a435868548",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "e7d702a9a9c389721beecee5c80e5068",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Distributed Systems Engineer — Full Time Main Office | OnSite Dedalus (YC S25) is hiring a full-time distributed systems engineer to help build the infrastructure layer powering the next generation of AI agents. We are building persistent compute infrastructure, cloud sandboxes, and developer tools for long-running AI agents. Our systems span virtualization, orchestration, storage, networking, and low-level runtime infrastructure. The role is based in San Francisco and involves working closely with a small, highly technical team operating at startup speed. WHAT YOU'LL WORK ON - Distributed systems infrastructure for large-scale agent workloads - Virtualization and sandboxing technologies - Persistent compute and storage systems - Scheduling, orchestration, and reliability engineering - Performance optimization across systems layers - Internal developer platforms and infrastructure tooling - Production systems operating under real-world scale and latency constraints REQUIREMENTS - Strong systems programming ability in Rust (preferred), Go, C/C++, or similar languages - Graduate-level knowledge of distributed systems and operating systems concepts - Experience building distributed systems in industry, research, or open source - Experience with Kubernetes and modern cloud infrastructure - Familiarity with one or more of the following: - distributed block storage - consistency models - virtualization and hypervisors - kernel or low-level systems architecture - Strong understanding of systems performance, reliability, and debugging NICE-TO-HAVE - Published systems research papers (NSDI, OSDI, SOSP, ATC, EuroSys, etc.) - Experience working on operating systems, kernels, or virtualization stacks - Contributions to open-source systems projects (Linux, Firecracker, Cloud Hypervisor, etc.) - Experience with low-level performance optimizatio",
          "matched_input": "kernel",
          "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/dedalus-labs/e71ec106-a376-42cb-88de-264c95d423ed",
          "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/dedalus-labs/e71ec106-a376-42cb-88de-264c95d423ed",
          "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/dedalus-labs/e71ec106-a376-42cb-88de-264c95d423ed",
          "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/dedalus-labs/e71ec106-a376-42cb-88de-264c95d423ed",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "f156e80d7bee2aa2f1ad3dfaeee795fb",
      "title": "Embedded Engineer (Video products)",
      "employer_name": "Ubiquiti",
      "employer_slug": "ubiquiti",
      "location_text": "Kyiv",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-03-25T13:16:33.000Z",
      "apply_url": "https://job-boards.greenhouse.io/ubiquiti/jobs/4195303009",
      "apply_url_verified": false,
      "ats": "greenhouse",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Embedded Engineer (Video products) Kyiv About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you'll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Requirements: 3+ years embedded firmware development experience with C / C++, Linux / Unix platform; Experience with ARM processors, embedded Linux; Experience working with H.265; Experience with Git, including merging and rebasing; Basic understanding of electronic circuits; Experience in embedded Linux systems (cross-build, flash, boot, system initialization, rootfs packaging, fault-tolerance, IPC, work with embedded filesystems), embedded distributions (Yocto,buildroot,OpenWRT); Good written and verbal English communication skills; Candidate needs to be in Kyiv (or consider relocation). Hybrid type of work. Will be a plus: Knowledge of Linux kernel; Experience with any SoC, preferrably multimedia-targeted; Video processing, streaming, encoding/decoding; Experience working with OpenCV; Image processing, tuning, enhancement; OOP/OOD, strong programming experience with C/C++; BS degree in Computer Science, or related engineering degree. Tools: ANSI C, Git, Linux kernel, embedded development tools (toolchain, OpenWRT, SW/HW debuggers, scripting). What do we offer: International work environment and work with global development teams; Excellent",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "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/1511737/000151173725000053/ubnt-20250630.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1511737/000151173725000053/ubnt-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": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": null,
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.890ab24799383b5fc6",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "f156e80d7bee2aa2f1ad3dfaeee795fb",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Embedded Engineer (Video products) Kyiv About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you'll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Requirements: 3+ years embedded firmware development experience with C / C++, Linux / Unix platform; Experience with ARM processors, embedded Linux; Experience working with H.265; Experience with Git, including merging and rebasing; Basic understanding of electronic circuits; Experience in embedded Linux systems (cross-build, flash, boot, system initialization, rootfs packaging, fault-tolerance, IPC, work with embedded filesystems), embedded distributions (Yocto,buildroot,OpenWRT); Good written and verbal English communication skills; Candidate needs to be in Kyiv (or consider relocation). Hybrid type of work. Will be a plus: Knowledge of Linux kernel; Experience with any SoC, preferrably multimedia-targeted; Video processing, streaming, encoding/decoding; Experience working with OpenCV; Image processing, tuning, enhancement; OOP/OOD, strong programming experience with C/C++; BS degree in Computer Science, or related engineering degree. Tools: ANSI C, Git, Linux kernel, embedded development tools (toolchain, OpenWRT, SW/HW debuggers, scripting). What do we offer: International work environment and work with global development teams; Excellent",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:f156e80d7bee2aa2f1ad3dfaeee795fb:description:kernel",
          "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.0442d15527fbaa411b",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "f156e80d7bee2aa2f1ad3dfaeee795fb",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Embedded Engineer (Video products) Kyiv About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you'll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Requirements: 3+ years embedded firmware development experience with C / C++, Linux / Unix platform; Experience with ARM processors, embedded Linux; Experience working with H.265; Experience with Git, including merging and rebasing; Basic understanding of electronic circuits; Experience in embedded Linux systems (cross-build, flash, boot, system initialization, rootfs packaging, fault-tolerance, IPC, work with embedded filesystems), embedded distributions (Yocto,buildroot,OpenWRT); Good written and verbal English communication skills; Candidate needs to be in Kyiv (or consider relocation). Hybrid type of work. Will be a plus: Knowledge of Linux kernel; Experience with any SoC, preferrably multimedia-targeted; Video processing, streaming, encoding/decoding; Experience working with OpenCV; Image processing, tuning, enhancement; OOP/OOD, strong programming experience with C/C++; BS degree in Computer Science, or related engineering degree. Tools: ANSI C, Git, Linux kernel, embedded development tools (toolchain, OpenWRT, SW/HW debuggers, scripting). What do we offer: International work environment and work with global development teams; Excellent",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1511737/000151173725000053/ubnt-20250630.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1511737/000151173725000053/ubnt-20250630.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": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://job-boards.greenhouse.io/ubiquiti/jobs/4195303009",
          "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/ubiquiti/jobs/4195303009",
          "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/ubiquiti/jobs/4195303009",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "7410f34c3135aebc3921507dba10d4ef",
      "title": "Head of Computer Vision and Machine Learning",
      "employer_name": "Dexterity",
      "employer_slug": "dexterity",
      "location_text": "Redwood City",
      "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": 160000,
      "salary_max": 220000,
      "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": 220000,
      "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": "2023-02-23T09:50:52.835Z",
      "apply_url": "https://jobs.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
      "apply_url_verified": false,
      "ats": "lever",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Head of Computer Vision and Machine Learning Redwood City About Dexterity: At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We're starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses around the world. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven, hardware-agnostic, and have already picked over 15 million goods in production. And did we mention we're customer-obsessed? Every decision, large and small, is driven by one question - how can we empower our customers with robots to do more than they thought was possible? Dexterity is one of the fastest growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We're a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality! Required Skills: MS or PhD in Computer Science, or a related discipline, or equivalent experience. 2 or more years of experience leading a team of Computer Vision or Machine Learning engineers. At least 5 years of experience in building ML datasets, data pipelines and serving architecture. Creating a culture of developing high quality models, tests and regressions Strong knowledge of Modern C++ and Python. Experience building, maintaining",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 47,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "base_salary_min"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "salary_period": {
          "field": "salary_period",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_period"
        },
        "equity_offered": {
          "field": "equity_offered",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "equity_offered"
        },
        "equity_included": {
          "field": "equity_included",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "equity_included"
        },
        "salary_currency": {
          "field": "salary_currency",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_currency"
        },
        "salary_disclosed": {
          "field": "salary_disclosed",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_disclosed"
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "visible_salary_max": {
          "field": "visible_salary_max",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "visible_salary_min": {
          "field": "visible_salary_min",
          "source": "derived:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": null,
      "role_function": "data",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "doctorate",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.79724e59cc9fe28ec1",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "7410f34c3135aebc3921507dba10d4ef",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:7410f34c3135aebc3921507dba10d4ef: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://jobs.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "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.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "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.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "source_values": [
            "derived:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.lever.co/dexterity/c09a7805-2a30-4f94-aaf4-4547fb619047",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "1e3fa6cf25306ee92b7ab4a9d7575b87",
      "title": "Staff/Sr. ML Compute Efficiency Engineer",
      "employer_name": "Apple",
      "employer_slug": "apple",
      "location_text": "Santa Clara, United States of America",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": 181100,
      "salary_max": 318400,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": "year",
      "base_salary_min": 181100,
      "base_salary_max": 318400,
      "salary_disclosed": true,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-01-23T22:26:07.510Z",
      "apply_url": "https://jobs.apple.com/en-us/details/200619215/staff-sr-ml-compute-efficiency-engineer?team=MLAI",
      "apply_url_verified": false,
      "ats": "apple_custom",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Staff/Sr. ML Compute Efficiency Engineer Santa Clara, United States of America Scaling machine learning workloads across thousands of GPUs and TPUs creates challenges that few engineers ever encounter. In Apple's Machine Learning Platform Technologies organization, we build the infrastructure that powers large-scale ML training and inference workloads, bringing together expertise in distributed systems, machine learning infrastructure, and high-performance computing. As a performance engineer in the ML Compute Efficiency team, you'll tackle ambiguous systems challenges, identify inefficiencies and build solutions that maximize accelerator utilization, reduce idle and fragmented capacity, and minimize recovery periods. This includes analyzing accelerator performance, digging into various parallelism techniques, and refining workload scheduling and orchestration across the compute fleet. Characterize ML workload behavior through profiling, benchmarks and metrics. Dive into unfamiliar codebases to prototype changes, evaluate tradeoffs, and build production-ready solutions. Design systems for efficient recovery from failures and preemptions. Create tools to identify and alert bottlenecks across applications and frameworks. Use workload-driven insights to influence next-generation hardware selection and procurement decisions. Collaborate closely with ML researchers and infrastructure engineers to address inefficiencies. Drive impact through hands-on contribution and mentorship. Minimum Qualifications: Experience with large-scale distributed systems for AI/ML workloads running on GPUs or TPUs. Strong software engineering skills with experience developing and optimizing training frameworks (e.g. PyTorch, JAX) using C/C++ or Python. Experience working on cross-functional projects with ML research and infrastructure teams. Familiarity with model architectures and various training techniques. Bachelor's degree in Computer Science or equivalent experience, with 7+ years of industry experience. Preferred",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 44,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "salary_max": {
          "field": "salary_max",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_max"
        },
        "salary_min": {
          "field": "salary_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "visa_sponsorship": {
          "field": "visa_sponsorship",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "visa_sponsorship"
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "staff_plus",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 7,
      "years_experience_max": 9,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 55,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": true,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.affdf95a4e8bf6faa5",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "1e3fa6cf25306ee92b7ab4a9d7575b87",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:1e3fa6cf25306ee92b7ab4a9d7575b87:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "salary_min": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200619215/staff-sr-ml-compute-efficiency-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/200619215/staff-sr-ml-compute-efficiency-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/200619215/staff-sr-ml-compute-efficiency-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/200619215/staff-sr-ml-compute-efficiency-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/200619215/staff-sr-ml-compute-efficiency-engineer?team=MLAI",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "company_stage": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.apple.com/en-us/details/200619215/staff-sr-ml-compute-efficiency-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": "0f9e1906f1aaaf4c39a0b10e176b0ea9",
      "title": "Platform Test Engineer",
      "employer_name": "Cisco",
      "employer_slug": "cisco",
      "location_text": "Bangalore, India",
      "country": "IN",
      "employment_type": "unknown",
      "remote_status": "hybrid",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": 2,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp",
        "profit_share"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-30T00:00:00.000Z",
      "apply_url": "https://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
      "apply_url_verified": true,
      "ats": "workday",
      "url_last_checked_alive": "2026-08-17T02:59:13.328Z",
      "removed_at": null,
      "description_excerpt": "Platform Test Engineer Bangalore, India Meet the Team Cisco SDWAN focuses on simplifying and securing enterprise WANs, enabling seamless cloud connectivity, automating network operations, and ensuring optimal application performance through advanced SD-WAN solutions. Our Team works on Cisco SD-WAN solutions that help enterprises build resilient, secure, and scalable wide area networks for distributed branch, cloud, and hybrid environments. The focus is on simplifying network operations through centralized management and automation, improving application and user experience with intelligent connectivity, and strengthening security with SASE-ready, zero-trust architecture. The team enables customers to connect sites, users, and cloud workloads with better visibility, performance, and operational efficiency. Your Impact Establish Define and drive the comprehensive test strategy and validation for the Cisco Secure Router Platform, including conducting deep-dive performance analysis to identify and resolve bottlenecks at the kernel, hardware-abstraction, data and control plane layers. As Platform Test engineer, you need to test Hardware, Software, Programmable and certify SFP/optics interoperable with Cisco Secure routers. Performance Debugging: Perform deep-dive analysis into performance bottlenecks at the kernel and hardware-abstraction layers including control plane. Design and evolve scalable test frameworks, test automation, and validation pipelines for both software and hardware. Collaborate with engineering leaders, product management, hardware, and TAC teams to define quality goals, test scope, and execution plan. Contribute to customer demos and technical presentations to showcase product and solution capabilities. Represent the test organization in cross-functional forums to influence release decisions, risk assessment, and quality metrics. Modern Test Practices: Utilize modern Test workflows, including AI-assisted coding",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.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"
        },
        "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_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 8,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.6399f5c130cbef75fa",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "0f9e1906f1aaaf4c39a0b10e176b0ea9",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Platform Test Engineer Bangalore, India Meet the Team Cisco SDWAN focuses on simplifying and securing enterprise WANs, enabling seamless cloud connectivity, automating network operations, and ensuring optimal application performance through advanced SD-WAN solutions. Our Team works on Cisco SD-WAN solutions that help enterprises build resilient, secure, and scalable wide area networks for distributed branch, cloud, and hybrid environments. The focus is on simplifying network operations through centralized management and automation, improving application and user experience with intelligent connectivity, and strengthening security with SASE-ready, zero-trust architecture. The team enables customers to connect sites, users, and cloud workloads with better visibility, performance, and operational efficiency. Your Impact Establish Define and drive the comprehensive test strategy and validation for the Cisco Secure Router Platform, including conducting deep-dive performance analysis to identify and resolve bottlenecks at the kernel, hardware-abstraction, data and control plane layers. As Platform Test engineer, you need to test Hardware, Software, Programmable and certify SFP/optics interoperable with Cisco Secure routers. Performance Debugging: Perform deep-dive analysis into performance bottlenecks at the kernel and hardware-abstraction layers including control plane. Design and evolve scalable test frameworks, test automation, and validation pipelines for both software and hardware. Collaborate with engineering leaders, product management, hardware, and TAC teams to define quality goals, test scope, and execution plan. Contribute to customer demos and technical presentations to showcase product and solution capabilities. Represent the test organization in cross-functional forums to influence release decisions, risk assessment, and quality metrics. Modern Test Practices: Utilize modern Test workflows, including AI-assisted coding",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:0f9e1906f1aaaf4c39a0b10e176b0ea9:description:kernel",
          "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.63e1bed29fb69172f1",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "0f9e1906f1aaaf4c39a0b10e176b0ea9",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Platform Test Engineer Bangalore, India Meet the Team Cisco SDWAN focuses on simplifying and securing enterprise WANs, enabling seamless cloud connectivity, automating network operations, and ensuring optimal application performance through advanced SD-WAN solutions. Our Team works on Cisco SD-WAN solutions that help enterprises build resilient, secure, and scalable wide area networks for distributed branch, cloud, and hybrid environments. The focus is on simplifying network operations through centralized management and automation, improving application and user experience with intelligent connectivity, and strengthening security with SASE-ready, zero-trust architecture. The team enables customers to connect sites, users, and cloud workloads with better visibility, performance, and operational efficiency. Your Impact Establish Define and drive the comprehensive test strategy and validation for the Cisco Secure Router Platform, including conducting deep-dive performance analysis to identify and resolve bottlenecks at the kernel, hardware-abstraction, data and control plane layers. As Platform Test engineer, you need to test Hardware, Software, Programmable and certify SFP/optics interoperable with Cisco Secure routers. Performance Debugging: Perform deep-dive analysis into performance bottlenecks at the kernel and hardware-abstraction layers including control plane. Design and evolve scalable test frameworks, test automation, and validation pipelines for both software and hardware. Collaborate with engineering leaders, product management, hardware, and TAC teams to define quality goals, test scope, and execution plan. Contribute to customer demos and technical presentations to showcase product and solution capabilities. Represent the test organization in cross-functional forums to influence release decisions, risk assessment, and quality metrics. Modern Test Practices: Utilize modern Test workflows, including AI-assisted coding",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.trust.apply.8a1e418a9f50ca7b1c",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "0f9e1906f1aaaf4c39a0b10e176b0ea9",
          "signal_type": "trust_signal",
          "display_text": "Apply link reachable when checked",
          "tooltip": "The apply URL was reachable during the last recorded crawl-time liveness check; this is not a live guarantee.",
          "source_binding": "row_trust_evidence",
          "source_field": "apply_url_verified",
          "source_value": true,
          "matched_input": true,
          "derivation_source": "verified_source_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "trust_source_exists",
          "counts_for_non_trivial_query": false,
          "truth_verified": true,
          "exact": true,
          "priority": 10,
          "mobile_priority": 11,
          "ui": {
            "icon": "ExternalLink",
            "tone": "verified",
            "href": null
          },
          "evidence_source": {
            "source_url": "https://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
            "source_label": "Apply link",
            "source_date": "2026-08-17T02:59:13.328Z"
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": "2026-08-17T02:59:13.328Z",
      "apply_url_verification_status": "reachable_when_last_checked",
      "apply_url_verification_label": "Reachable when checked at 2026-08-17T02:59:13.328Z",
      "field_source_signals": {
        "remote_status": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
          "source_values": [
            "rule:remote_status"
          ],
          "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/858877/000085887725000111/csco-20250726.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.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://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
          "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://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
          "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://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Platform-Test-Engineer_2011906",
          "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": "a0f8b23a6ba6bb8fd5796029736676c6",
      "title": "Computer Scientist 2 (C++)",
      "employer_name": "Adobe Inc.",
      "employer_slug": "adobe",
      "location_text": "Noida",
      "country": "IN",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-06-08T00:00:00.000Z",
      "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Noida/Computer-Scientist-2--C---_R167185-1",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Computer Scientist 2 (C++) Noida posted: Posted 4 Days Ago",
      "parental_leave_weeks": 16,
      "non_birth_parent_leave_weeks": 16,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 90,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "parental_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.1b42640166f1e50913",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "a0f8b23a6ba6bb8fd5796029736676c6",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:a0f8b23a6ba6bb8fd5796029736676c6:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm"
          ],
          "checked_at": null
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Noida/Computer-Scientist-2--C---_R167185-1",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Noida/Computer-Scientist-2--C---_R167185-1",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-05-07"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Noida/Computer-Scientist-2--C---_R167185-1",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Noida/Computer-Scientist-2--C---_R167185-1",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": null,
          "source_values": [
            "source_sector"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "21c47244ffcbfcaba3b8a626b15f6115",
      "title": "Supercomputing Engineer (Network)",
      "employer_name": "Etched",
      "employer_slug": "etched",
      "location_text": "San Jose, CA, United States",
      "country": "US",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 6,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "USD",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": null,
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": true,
      "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": "2025-06-11T05:17:38.541Z",
      "apply_url": "https://jobs.ashbyhq.com/etched/245b1caa-dfbc-45e6-91df-b0741acab501",
      "apply_url_verified": false,
      "ats": "ashby",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Supercomputing Engineer (Network) San Jose, CA, United States About Etched Etched is building the world's first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are seeking highly motivated and skilled Supercomputing Engineers (Network) to join our team. This team plays a critical role in developing, qualifying, and optimizing high-performance networking solutions for large-scale inference workloads. As a Pod Software Engineer, you will focus on developing and qualifying software that drives communication amongst Sohu inference nodes in multi-rack inference clusters. You will collaborate closely with kernel, platform, and telemetry teams to push the boundaries of peer-to-peer RDMA efficiency. Key Responsibilities - Design, develop, and implement RDMA based networking peering, supporting high bandwidth, low latency communication across PCIe nodes within and across racks. Includes work across Operating System, kernel drivers, embedded software and system software. - Develop tests that qualify host processors (x86),. NICs, TORs and device network interfaces for high performance. - Furnish burn-in teams with tests that represent both real-world use cases and workloads for device to device networking, and extreme-load stress testing. - Define the key metrics that system software must",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 43,
      "benefit_verified": false,
      "benefit_last_verified": null,
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "role_family": {
          "field": "role_family",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_family"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "mental_health_support": {
          "field": "mental_health_support",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "mental_health_support"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": null,
      "employer_industry_source": null,
      "employer_size": "51-200",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.7864a9c104649be3b2",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "21c47244ffcbfcaba3b8a626b15f6115",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Supercomputing Engineer (Network) San Jose, CA, United States About Etched Etched is building the world's first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are seeking highly motivated and skilled Supercomputing Engineers (Network) to join our team. This team plays a critical role in developing, qualifying, and optimizing high-performance networking solutions for large-scale inference workloads. As a Pod Software Engineer, you will focus on developing and qualifying software that drives communication amongst Sohu inference nodes in multi-rack inference clusters. You will collaborate closely with kernel, platform, and telemetry teams to push the boundaries of peer-to-peer RDMA efficiency. Key Responsibilities - Design, develop, and implement RDMA based networking peering, supporting high bandwidth, low latency communication across PCIe nodes within and across racks. Includes work across Operating System, kernel drivers, embedded software and system software. - Develop tests that qualify host processors (x86),. NICs, TORs and device network interfaces for high performance. - Furnish burn-in teams with tests that represent both real-world use cases and workloads for device to device networking, and extreme-load stress testing. - Define the key metrics that system software must",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:21c47244ffcbfcaba3b8a626b15f6115:description:kernel",
          "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.127a4cbfc38db16a75",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "21c47244ffcbfcaba3b8a626b15f6115",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Supercomputing Engineer (Network) San Jose, CA, United States About Etched Etched is building the world's first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are seeking highly motivated and skilled Supercomputing Engineers (Network) to join our team. This team plays a critical role in developing, qualifying, and optimizing high-performance networking solutions for large-scale inference workloads. As a Pod Software Engineer, you will focus on developing and qualifying software that drives communication amongst Sohu inference nodes in multi-rack inference clusters. You will collaborate closely with kernel, platform, and telemetry teams to push the boundaries of peer-to-peer RDMA efficiency. Key Responsibilities - Design, develop, and implement RDMA based networking peering, supporting high bandwidth, low latency communication across PCIe nodes within and across racks. Includes work across Operating System, kernel drivers, embedded software and system software. - Develop tests that qualify host processors (x86),. NICs, TORs and device network interfaces for high performance. - Furnish burn-in teams with tests that represent both real-world use cases and workloads for device to device networking, and extreme-load stress testing. - Define the key metrics that system software must",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        }
      ],
      "parental_leave_source_label": null,
      "k401_match_source_label": null,
      "k401_contribution_source_label": null,
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/etched/245b1caa-dfbc-45e6-91df-b0741acab501",
          "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/etched/245b1caa-dfbc-45e6-91df-b0741acab501",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "mental_health_support": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://jobs.ashbyhq.com/etched/245b1caa-dfbc-45e6-91df-b0741acab501",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        }
      }
    },
    {
      "id": "6a6fbf83e5776a4f454e545465606547",
      "title": "Lead Engineer – Embedded Software Development (M/F/D)",
      "employer_name": "Baker Hughes",
      "employer_slug": "baker-hughes",
      "location_text": "PL-PDK-WARSAW-ALEJA KRAKOWSKA 110/114 BLD 3014613",
      "country": "PL",
      "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": "2026-06-12T00:00:00.000Z",
      "apply_url": "https://bakerhughes.wd5.myworkdayjobs.com/BakerHughes/job/PL-PDK-WARSAW-ALEJA-KRAKOWSKA-110114-BLD-3014613/Lead-Engineer---Embedded-Software-Development_R164226-1",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Lead Engineer – Embedded Software Development (M/F/D) PL-PDK-WARSAW-ALEJA KRAKOWSKA 110/114 BLD 3014613 posted: Posted Today",
      "parental_leave_weeks": 12,
      "non_birth_parent_leave_weeks": 8,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 81,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1701605/000170160526000007/bkr-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/1701605/000170160526000007/bkr-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave",
          "db_column": "parental_leave_weeks",
          "source_url": "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave"
        }
      },
      "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": "Energy",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.a041ffb6b825cdc4ee",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "6a6fbf83e5776a4f454e545465606547",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:6a6fbf83e5776a4f454e545465606547:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/1701605/000170160526000007/bkr-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/1701605/000170160526000007/bkr-20251231.htm"
          ],
          "checked_at": null
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://bakerhughes.wd5.myworkdayjobs.com/BakerHughes/job/PL-PDK-WARSAW-ALEJA-KRAKOWSKA-110114-BLD-3014613/Lead-Engineer---Embedded-Software-Development_R164226-1",
          "source_values": [
            "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://bakerhughes.wd5.myworkdayjobs.com/BakerHughes/job/PL-PDK-WARSAW-ALEJA-KRAKOWSKA-110114-BLD-3014613/Lead-Engineer---Embedded-Software-Development_R164226-1",
          "source_values": [
            "https://www.bakerhughesbenefits.com/faq-categories/paid-parental-leave"
          ],
          "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://bakerhughes.wd5.myworkdayjobs.com/BakerHughes/job/PL-PDK-WARSAW-ALEJA-KRAKOWSKA-110114-BLD-3014613/Lead-Engineer---Embedded-Software-Development_R164226-1",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://bakerhughes.wd5.myworkdayjobs.com/BakerHughes/job/PL-PDK-WARSAW-ALEJA-KRAKOWSKA-110114-BLD-3014613/Lead-Engineer---Embedded-Software-Development_R164226-1",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": null,
          "source_values": [
            "source_sector"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "26b180f141b500b83aa3751c81e1d11b",
      "title": "Embedded Software Engineer",
      "employer_name": "Methode Electronics INC",
      "employer_slug": "methode-electronics",
      "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": "base",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": false,
      "equity_included_source": null,
      "equity_type": [
        "none"
      ],
      "k401_match": "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": 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://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
      "apply_url_verified": true,
      "ats": "workday",
      "url_last_checked_alive": "2026-08-17T02:59:13.328Z",
      "removed_at": null,
      "description_excerpt": "Embedded Software Engineer 2 Locations About the role You will design, implement, and validate embedded software for rugged, industrial wireless control systems used in heavy equipment and safety‑critical environments. The work spans platform bring‑up through application features, with close collaboration across hardware, RF, compliance, and manufacturing teams. Our products emphasize reliability, functional safety, and secure‑by‑design practices throughout the lifecycle. What you'll do Develop firmware (C/C++, RTOS/Linux) including bootloader, BSP, device drivers, and application logic. Develop in C/C++ on RTOS and/or embedded Linux (Yocto/Buildroot) targets; contribute to device trees, kernel modules, and HALs where needed. Implement and document wired/wireless interfaces (CAN / J1939, UART, SPI, I²C; Bluetooth where applicable); integrate with RF and baseband teams. Apply coding standards and peer reviews; participate in design and module testing aligned with our R&D programming standards. Create verification plans; automate unit/integration tests; support environmental/EMC/functional tests in our labs; triage field issues with production & service. Contribute to secure-by-design and functional safety lifecycle activities (requirements, architecture, verification, validation, documentation). Understanding of functional safety concepts (IEC/ISO frameworks). Ability to contribute to safety requirements, verification evidence, traceability, and safety analyses. Collaborate with hardware, RF, mechanical, and compliance teams. Minimum qualifications Bachelor's in Computer, Electrical, or Software Engineering (or equivalent practical experience). 3+ years developing embedded software in C/C++; demonstrated experience with low‑level drivers and real‑time constraints. Hands‑on debugging with oscilloscopes, logic analyzers, JTAG/SWD, and profilers; strong problem‑solving and ownership. Preferred qualifications Experience with Yocto, bootloaders, kernel configuration, device trees, and OTA/secure update mechanisms. Industrial comms (CAN/J1939, PROFINET),",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "company_stage": {
          "field": "company_stage",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "company_stage"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "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"
        },
        "mental_health_support": {
          "field": "mental_health_support",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "mental_health_support"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "llm:greenfield:inv_371_postfix",
      "company_stage": "public-company",
      "company_stage_source": "llm:greenfield:inv_371_postfix",
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 45,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.b2e9995755f24d686d",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "26b180f141b500b83aa3751c81e1d11b",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Embedded Software Engineer 2 Locations About the role You will design, implement, and validate embedded software for rugged, industrial wireless control systems used in heavy equipment and safety‑critical environments. The work spans platform bring‑up through application features, with close collaboration across hardware, RF, compliance, and manufacturing teams. Our products emphasize reliability, functional safety, and secure‑by‑design practices throughout the lifecycle. What you'll do Develop firmware (C/C++, RTOS/Linux) including bootloader, BSP, device drivers, and application logic. Develop in C/C++ on RTOS and/or embedded Linux (Yocto/Buildroot) targets; contribute to device trees, kernel modules, and HALs where needed. Implement and document wired/wireless interfaces (CAN / J1939, UART, SPI, I²C; Bluetooth where applicable); integrate with RF and baseband teams. Apply coding standards and peer reviews; participate in design and module testing aligned with our R&D programming standards. Create verification plans; automate unit/integration tests; support environmental/EMC/functional tests in our labs; triage field issues with production & service. Contribute to secure-by-design and functional safety lifecycle activities (requirements, architecture, verification, validation, documentation). Understanding of functional safety concepts (IEC/ISO frameworks). Ability to contribute to safety requirements, verification evidence, traceability, and safety analyses. Collaborate with hardware, RF, mechanical, and compliance teams. Minimum qualifications Bachelor's in Computer, Electrical, or Software Engineering (or equivalent practical experience). 3+ years developing embedded software in C/C++; demonstrated experience with low‑level drivers and real‑time constraints. Hands‑on debugging with oscilloscopes, logic analyzers, JTAG/SWD, and profilers; strong problem‑solving and ownership. Preferred qualifications Experience with Yocto, bootloaders, kernel configuration, device trees, and OTA/secure update mechanisms. Industrial comms (CAN/J1939, PROFINET),",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:26b180f141b500b83aa3751c81e1d11b:description:kernel",
          "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.205329a5505f4e8318",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "26b180f141b500b83aa3751c81e1d11b",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "description_excerpt",
          "source_value": "Embedded Software Engineer 2 Locations About the role You will design, implement, and validate embedded software for rugged, industrial wireless control systems used in heavy equipment and safety‑critical environments. The work spans platform bring‑up through application features, with close collaboration across hardware, RF, compliance, and manufacturing teams. Our products emphasize reliability, functional safety, and secure‑by‑design practices throughout the lifecycle. What you'll do Develop firmware (C/C++, RTOS/Linux) including bootloader, BSP, device drivers, and application logic. Develop in C/C++ on RTOS and/or embedded Linux (Yocto/Buildroot) targets; contribute to device trees, kernel modules, and HALs where needed. Implement and document wired/wireless interfaces (CAN / J1939, UART, SPI, I²C; Bluetooth where applicable); integrate with RF and baseband teams. Apply coding standards and peer reviews; participate in design and module testing aligned with our R&D programming standards. Create verification plans; automate unit/integration tests; support environmental/EMC/functional tests in our labs; triage field issues with production & service. Contribute to secure-by-design and functional safety lifecycle activities (requirements, architecture, verification, validation, documentation). Understanding of functional safety concepts (IEC/ISO frameworks). Ability to contribute to safety requirements, verification evidence, traceability, and safety analyses. Collaborate with hardware, RF, mechanical, and compliance teams. Minimum qualifications Bachelor's in Computer, Electrical, or Software Engineering (or equivalent practical experience). 3+ years developing embedded software in C/C++; demonstrated experience with low‑level drivers and real‑time constraints. Hands‑on debugging with oscilloscopes, logic analyzers, JTAG/SWD, and profilers; strong problem‑solving and ownership. Preferred qualifications Experience with Yocto, bootloaders, kernel configuration, device trees, and OTA/secure update mechanisms. Industrial comms (CAN/J1939, PROFINET),",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.trust.apply.e144a4fc2b3638da9e",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "26b180f141b500b83aa3751c81e1d11b",
          "signal_type": "trust_signal",
          "display_text": "Apply link reachable when checked",
          "tooltip": "The apply URL was reachable during the last recorded crawl-time liveness check; this is not a live guarantee.",
          "source_binding": "row_trust_evidence",
          "source_field": "apply_url_verified",
          "source_value": true,
          "matched_input": true,
          "derivation_source": "verified_source_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "trust_source_exists",
          "counts_for_non_trivial_query": false,
          "truth_verified": true,
          "exact": true,
          "priority": 10,
          "mobile_priority": 11,
          "ui": {
            "icon": "ExternalLink",
            "tone": "verified",
            "href": null
          },
          "evidence_source": {
            "source_url": "https://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
            "source_label": "Apply link",
            "source_date": "2026-08-17T02:59:13.328Z"
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": "2026-08-17T02:59:13.328Z",
      "apply_url_verification_status": "reachable_when_last_checked",
      "apply_url_verification_label": "Reachable when checked at 2026-08-17T02:59:13.328Z",
      "field_source_signals": {
        "salary_type": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "equity_included": {
          "tier": "inferred",
          "verified": false,
          "label": "Inferred - source not recorded",
          "source_label": "source not recorded",
          "href": null,
          "source_values": [],
          "checked_at": "2026-06-20T05:42:05.724Z"
        },
        "k401_match": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "source_values": [
            "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://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "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://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "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://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "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"
        },
        "mental_health_support": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://methode.wd5.myworkdayjobs.com/methode/job/Oklahoma-City-OK/Embedded-Software-Engineer-1_R24351",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": "2026-06-13T01:18:42.546Z"
        }
      }
    },
    {
      "id": "3dc25e14a8f973c555353d7b325351b3",
      "title": "Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore",
      "employer_name": "Cisco",
      "employer_slug": "cisco",
      "location_text": "Bangalore, India",
      "country": "IN",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp",
        "profit_share"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-06-11T00:00:00.000Z",
      "apply_url": "https://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Software-Engineering-Technical-Leader_2012500",
      "apply_url_verified": true,
      "ats": "workday",
      "url_last_checked_alive": "2026-08-17T02:59:13.328Z",
      "removed_at": null,
      "description_excerpt": "Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore Bangalore, India Meet the Team The Common Hardware Group (CHG) at Cisco is seeking skilled software engineers to join our Diagnostic/BSP team, responsible for ensuring the reliability and performance of our world-class hardware. Our team develops software for Cisco's network switches and routers, which feature advanced application awareness to build a flexible and agile network infrastructure. These capabilities support multi-layered responses to the diverse workload demands of AI and ML. This is a unique opportunity to grow your technical skill set and gain visibility and recognition across cross-functional teams within Cisco. We value motivated individuals who enjoy solving complex challenges and thrive in a collaborative, innovative environment. Your Impact Architect and develop BIOS, BSP, and diagnostics for Cisco's Core and Edge routing products. Design, develop, and test device drivers for FPGA and high-speed networking peripherals. Develop and execute software test plans. Collaborate with cross-functional teams to debug prototypes and validate software. Innovate and drive unique software, hardware, and technology solutions with a global impact on Cisco's product portfolio. Utilize deep technical expertise for complex consultations and act as an expert both internally and externally. Shape technology and industry trends to enable a competitive advantage and ensure long-term business impact. Minimum Qualifications Bachelor's degree in Electrical Engineering, Computer Science, or related field with 15+ years experience, or Master's degree with 12+ years experience. Current experience in C, C++, and Python programming for embedded systems.",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-13T01:18:42.546Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": "2026-06-20T05:42:05.724Z",
      "llm_extraction_run_id": "postfix_final_004037",
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "years_min": {
          "field": "years_min",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "years_experience_min"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "tech_stack": {
          "field": "tech_stack",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "tech_stack"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "customer_type": {
          "field": "customer_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "customer_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "industry_vertical": {
          "field": "industry_vertical",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "industry_vertical"
        },
        "naics_sector_code": {
          "field": "naics_sector_code",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_code"
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "naics_sector_title": {
          "field": "naics_sector_title",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "naics_sector_title"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 10,
      "years_experience_max": 15,
      "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": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "bachelors",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.query.description_excerpt.6a220cb06af9ff61db",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "3dc25e14a8f973c555353d7b325351b3",
          "signal_type": "query_match",
          "display_text": "Description: \"kernel\"",
          "tooltip": "Description matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "description_excerpt",
          "source_value": "Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore Bangalore, India Meet the Team The Common Hardware Group (CHG) at Cisco is seeking skilled software engineers to join our Diagnostic/BSP team, responsible for ensuring the reliability and performance of our world-class hardware. Our team develops software for Cisco's network switches and routers, which feature advanced application awareness to build a flexible and agile network infrastructure. These capabilities support multi-layered responses to the diverse workload demands of AI and ML. This is a unique opportunity to grow your technical skill set and gain visibility and recognition across cross-functional teams within Cisco. We value motivated individuals who enjoy solving complex challenges and thrive in a collaborative, innovative environment. Your Impact Architect and develop BIOS, BSP, and diagnostics for Cisco's Core and Edge routing products. Design, develop, and test device drivers for FPGA and high-speed networking peripherals. Develop and execute software test plans. Collaborate with cross-functional teams to debug prototypes and validate software. Innovate and drive unique software, hardware, and technology solutions with a global impact on Cisco's product portfolio. Utilize deep technical expertise for complex consultations and act as an expert both internally and externally. Shape technology and industry trends to enable a competitive advantage and ensure long-term business impact. Minimum Qualifications Bachelor's degree in Electrical Engineering, Computer Science, or related field with 15+ years experience, or Master's degree with 12+ years experience. Current experience in C, C++, and Python programming for embedded systems.",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:3dc25e14a8f973c555353d7b325351b3:description:kernel",
          "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.6d0f071ba52ca72349",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "3dc25e14a8f973c555353d7b325351b3",
          "signal_type": "query_match",
          "display_text": "Title: \"kernel\"",
          "tooltip": "Title matched \"kernel\" from your search.",
          "source_binding": "bm25_field_evidence",
          "source_field": "title",
          "source_value": "Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:3dc25e14a8f973c555353d7b325351b3:title:kernel",
          "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.c8ba849e464d452d25",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "3dc25e14a8f973c555353d7b325351b3",
          "signal_type": "query_match",
          "display_text": "Title: \"kernel\"",
          "tooltip": "Title contains \"kernel\" from your search.",
          "source_binding": "token_match",
          "source_field": "title",
          "source_value": "Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore",
          "matched_input": "kernel",
          "derivation_source": "row_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "row_field_contains",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": true,
          "priority": 80,
          "mobile_priority": 2,
          "ui": {
            "icon": "SearchCheck",
            "tone": "match",
            "href": null
          }
        },
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.trust.apply.aac25d48e8fea4f4df",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "3dc25e14a8f973c555353d7b325351b3",
          "signal_type": "trust_signal",
          "display_text": "Apply link reachable when checked",
          "tooltip": "The apply URL was reachable during the last recorded crawl-time liveness check; this is not a live guarantee.",
          "source_binding": "row_trust_evidence",
          "source_field": "apply_url_verified",
          "source_value": true,
          "matched_input": true,
          "derivation_source": "verified_source_field",
          "candidate_evidence_id": null,
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "trust_source_exists",
          "counts_for_non_trivial_query": false,
          "truth_verified": true,
          "exact": true,
          "priority": 10,
          "mobile_priority": 11,
          "ui": {
            "icon": "ExternalLink",
            "tone": "verified",
            "href": null
          },
          "evidence_source": {
            "source_url": "https://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Software-Engineering-Technical-Leader_2012500",
            "source_label": "Apply link",
            "source_date": "2026-08-17T02:59:13.328Z"
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": "2026-08-17T02:59:13.328Z",
      "apply_url_verification_status": "reachable_when_last_checked",
      "apply_url_verification_label": "Reachable when checked at 2026-08-17T02:59:13.328Z",
      "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/858877/000085887725000111/csco-20250726.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/858877/000085887725000111/csco-20250726.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://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Software-Engineering-Technical-Leader_2012500",
          "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://cisco.wd5.myworkdayjobs.com/Cisco_Careers/job/Bangalore-India/Software-Engineering-Technical-Leader_2012500",
          "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": "9478389ec219ad4374a646e3dc664cdb",
      "title": "Senior Machine Learning Engineer",
      "employer_name": "Adobe Inc.",
      "employer_slug": "adobe",
      "location_text": "3 Locations",
      "country": "unknown",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "espp"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-05-12T00:00:00.000Z",
      "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334",
      "apply_url_verified": false,
      "ats": "workday",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Senior Machine Learning Engineer 3 Locations posted: Posted 30+ Days Ago",
      "parental_leave_weeks": 16,
      "non_birth_parent_leave_weeks": 16,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 90,
      "benefit_verified": true,
      "benefit_last_verified": "2026-05-07",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        },
        "parental_leave_weeks": {
          "field": "parental_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "parental_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        },
        "non_birth_parent_leave_weeks": {
          "field": "non_birth_parent_leave_weeks",
          "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence",
          "db_column": "non_birth_parent_leave_weeks",
          "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence"
        }
      },
      "seniority": "senior",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 5,
      "years_experience_max": 9,
      "role_function": "data",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Technology",
      "employer_industry_source": "source_sector",
      "employer_size": "5000+",
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.4069e003670034adb5",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "9478389ec219ad4374a646e3dc664cdb",
          "signal_type": "query_match",
          "display_text": "Role: semantic match",
          "tooltip": "Role provided semantic evidence for your search intent.",
          "source_binding": "vector_semantic_evidence",
          "source_field": "role_function",
          "source_value": "data",
          "matched_input": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:9478389ec219ad4374a646e3dc664cdb:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": "Employer benefits source",
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm"
          ],
          "checked_at": null
        },
        "parental_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "non_birth_parent_leave_weeks": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334",
          "source_values": [
            "https://benefits.adobe.com/us/time-off/leaves-of-absence"
          ],
          "checked_at": "2026-05-07"
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-05-07"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Francisco/Senior-Machine-Learning-Engineer_R166334",
          "source_values": [
            "rule"
          ],
          "checked_at": null
        },
        "employer_industry": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": null,
          "source_values": [
            "source_sector"
          ],
          "checked_at": null
        }
      }
    },
    {
      "id": "03a048320090d6496cca34ac745b99bd",
      "title": "Python and PySpark Developer",
      "employer_name": "Citigroup Inc.",
      "employer_slug": "citigroup",
      "location_text": "Chennai, Tamil Nādu, India",
      "country": "IN",
      "employment_type": "unknown",
      "remote_status": "unspecified",
      "remote_status_source": null,
      "remote_status_enriched_at": null,
      "days_in_office": null,
      "timezone_overlap_hours": 3,
      "salary_min": null,
      "salary_max": null,
      "salary_min_source": null,
      "salary_max_source": null,
      "salary_currency": "UNSPECIFIED",
      "salary_type": "unknown",
      "salary_type_source": null,
      "salary_type_enriched_at": null,
      "salary_period": null,
      "base_salary_min": null,
      "base_salary_max": null,
      "salary_disclosed": false,
      "equity_included": true,
      "equity_included_source": null,
      "equity_type": [
        "rsu",
        "options",
        "profit_share"
      ],
      "k401_match": "yes",
      "match_401k_pct": null,
      "match_401k_pct_source": null,
      "k401_match_source_url": null,
      "k401_match_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "k401_contribution_source_url": null,
      "k401_contribution_source_fields": [
        "EMPLR_CONTRIB_INCOME_AMT"
      ],
      "profit_sharing": false,
      "bonus_offered": false,
      "mental_health_support": null,
      "childcare_subsidy": null,
      "fertility_family_building_benefits": null,
      "adoption_assistance_offered": null,
      "surrogacy_assistance_offered": null,
      "student_loan_repayment_offered": null,
      "learning_budget_offered": null,
      "relocation_assistance": null,
      "top_startup_sources": [],
      "posted_at": "2026-06-12T10:25:24.000Z",
      "apply_url": "https://citi.eightfold.ai/careers/job/859035678337",
      "apply_url_verified": false,
      "ats": "eightfold",
      "url_last_checked_alive": null,
      "removed_at": null,
      "description_excerpt": "Python and PySpark Developer Chennai, Tamil Nādu, India",
      "parental_leave_weeks": null,
      "non_birth_parent_leave_weeks": null,
      "parental_leave_weeks_source": null,
      "non_birth_parent_leave_weeks_source": null,
      "parental_leave_source_url": null,
      "pto_days": null,
      "unlimited_pto": false,
      "sabbatical_eligible": false,
      "family_friendly_score": 40,
      "benefit_verified": true,
      "benefit_last_verified": "2026-06-07T00:00:00Z",
      "hire_states_allowed": [],
      "state_eligibility_source": null,
      "state_eligibility_enriched_at": null,
      "llm_quality_pass_at": null,
      "llm_signals_at": null,
      "llm_extraction_run_id": null,
      "llm_extraction_extracted_at": null,
      "llm_extraction_field_sources": {
        "seniority": {
          "field": "seniority",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "seniority"
        },
        "k401_match": {
          "source": "dol_form_5500",
          "source_url": null,
          "source_fields": [
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "source_label": "DOL Form 5500 filing"
        },
        "equity_type": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "salary_type": {
          "field": "salary_type",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "salary_type"
        },
        "role_function": {
          "field": "role_function",
          "source": "rule",
          "db_column": "role_function"
        },
        "equity_included": {
          "source": "sec_10k",
          "source_url": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm",
          "source_fields": [
            "equity_offered",
            "equity_type"
          ]
        },
        "education_required": {
          "field": "education_required",
          "source": "llm:greenfield:inv_371_postfix",
          "db_column": "education_required"
        }
      },
      "seniority": "mid",
      "seniority_source": "llm:greenfield:inv_371_postfix",
      "years_experience_min": 3,
      "years_experience_max": 7,
      "role_function": "engineering",
      "role_function_source": "rule",
      "company_stage": null,
      "company_stage_source": null,
      "employer_industry": "Finance",
      "employer_industry_source": "source_sector",
      "employer_size": null,
      "quality_score": 35,
      "travel_pct": null,
      "requires_shift": null,
      "shift_type": "unknown",
      "shift_type_source": null,
      "weekend_work": "unknown",
      "weekend_work_source": null,
      "relocation_assistance_source": null,
      "contractor_w2": "unknown",
      "required_timezone": null,
      "fertility_family_building_benefits_source": null,
      "mental_health_support_source": null,
      "adoption_assistance_offered_source": null,
      "childcare_subsidy_source": null,
      "learning_budget_offered_source": null,
      "surrogacy_assistance_offered_source": null,
      "cover_letter_required": null,
      "cover_letter_required_source": null,
      "assessment_required": null,
      "assessment_required_source": null,
      "application_deadline": null,
      "application_deadline_source": null,
      "visa_sponsorship": false,
      "us_citizenship_required": false,
      "security_clearance": "none",
      "education_required": "none",
      "roll_up_count": null,
      "roll_up_total_locations": null,
      "explanations": [
        {
          "schema_version": "inv382.match_signal.v1",
          "signal_id": "sig.semantic.role_function.991d6da7cade23ce55",
          "query_id": "gq_66eb6347ba344c23e0fd",
          "job_id": "03a048320090d6496cca34ac745b99bd",
          "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": "kernel",
          "derivation_source": "candidate_result.raw_match_evidence",
          "candidate_evidence_id": "ev:gq_66eb6347ba344c23e0fd:03a048320090d6496cca34ac745b99bd:vector",
          "rerank_evidence_id": null,
          "taxonomy_alias_id": null,
          "oracle_verification_method": "candidate_evidence_exists",
          "counts_for_non_trivial_query": true,
          "truth_verified": true,
          "exact": false,
          "priority": 74,
          "mobile_priority": 2,
          "ui": {
            "icon": "Sparkles",
            "tone": "match",
            "href": null
          }
        }
      ],
      "source_label": "DOL Form 5500 filing",
      "parental_leave_source_label": null,
      "k401_match_source_label": "DOL Form 5500 filing",
      "k401_contribution_source_label": "DOL Form 5500 filing",
      "apply_url_checked_at": null,
      "apply_url_verification_status": "not_reachable_or_not_checked",
      "apply_url_verification_label": "Not checked or not reachable at last crawl",
      "field_source_signals": {
        "equity_included": {
          "tier": "government",
          "verified": true,
          "label": "Verified - SEC 10-K",
          "source_label": "SEC 10-K",
          "href": "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm",
          "source_values": [
            "sec_10k",
            "https://www.sec.gov/Archives/edgar/data/831001/000083100126000011/c-20251231.htm"
          ],
          "checked_at": null
        },
        "k401_match": {
          "tier": "government",
          "verified": true,
          "label": "Verified - DOL Form 5500",
          "source_label": "DOL Form 5500",
          "href": null,
          "source_values": [
            "dol_form_5500",
            "EMPLR_CONTRIB_INCOME_AMT"
          ],
          "checked_at": "2026-06-07T00:00:00Z"
        },
        "seniority": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://citi.eightfold.ai/careers/job/859035678337",
          "source_values": [
            "llm:greenfield:inv_371_postfix"
          ],
          "checked_at": null
        },
        "role_function": {
          "tier": "posting",
          "verified": true,
          "label": "From the posting",
          "source_label": "the posting",
          "href": "https://citi.eightfold.ai/careers/job/859035678337",
          "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
        }
      }
    }
  ],
  "total": 494,
  "page": 14,
  "per_page": 24,
  "applied_filters": {
    "q": "KERNEL"
  },
  "hidden_unknown_benefits_count": 0,
  "hidden_quality_floor_count": 0,
  "quality_floor": "default",
  "search_profile": {
    "profile_id": "inv382.d6.pg_textsearch_bge_small_rrf.v1",
    "bm25_extension": "pg_textsearch",
    "vector_model": "BAAI/bge-small-en-v1.5",
    "vector_model_version": "v1.5",
    "fusion_method": "rrf"
  },
  "explanation_context": {
    "non_trivial_query": false,
    "query_terms": [
      "kernel"
    ],
    "active_filter_keys": [],
    "visible_signal_limit": 3,
    "visible_trust_limit": 2
  },
  "event_context": {
    "query_context": {
      "query_id": "b1fd15b2-7d33-4ce2-a5c8-221a8d5000a9",
      "issued_at": "2026-08-22T01:04:00.289Z",
      "route": "/jobs",
      "page": 14,
      "per_page": 24,
      "total_results": 494,
      "sort": "relevance",
      "ranking_policy": "hybrid_rrf_rerank",
      "ranking_policy_version": "inv382.jobs.search.v2",
      "query_hash": "hmac_sha256:0LuO8hbKwiSPDLWH2KrX4ZTyKdtZxwx0euwulc8sABU",
      "filter_hash": "hmac_sha256:6CBErDPXOFVCSNkSGbTmuw6GxoMjwSLro0KqZMtxL_0",
      "query_features": {
        "has_q": true,
        "q_term_count": 1,
        "q_length_bucket": "1_15",
        "q_pii_redacted": false,
        "state_count": 0,
        "benefit_filters": [],
        "quality_floor": "default"
      },
      "exposures": [
        {
          "result_id": "bc30f92bf8a07da236ca7e6c1835d8e5",
          "position": 313,
          "page_position": 1,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.003787878787878788,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 72,
            "quality_score": 55
          }
        },
        {
          "result_id": "011bde266387b45b3977c297b51573dd",
          "position": 314,
          "page_position": 2,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34702149945369254,
            "rrf_score": 0.003787878787878788,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 102,
            "quality_score": 35
          }
        },
        {
          "result_id": "c53738d5934d42e8ec71a07ea0191faf",
          "position": 315,
          "page_position": 3,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.0037735849056603774,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 70,
            "quality_score": 45
          }
        },
        {
          "result_id": "6a5aaa9345090f83df9983da6e47db1d",
          "position": 316,
          "page_position": 4,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34704847967046737,
            "rrf_score": 0.0037735849056603774,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 74,
            "quality_score": 35
          }
        },
        {
          "result_id": "cc5495b1444e1136cae6fa38e90e033e",
          "position": 317,
          "page_position": 5,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3470668987313811,
            "rrf_score": 0.0037593984962406013,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 89,
            "quality_score": 35
          }
        },
        {
          "result_id": "cc18e70019c232c706fb0b8570ae823b",
          "position": 318,
          "page_position": 6,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.0037593984962406013,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 379,
            "quality_score": 45
          }
        },
        {
          "result_id": "0930c2382c4b1757258c46c18e9354e0",
          "position": 319,
          "page_position": 7,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34710697250920586,
            "rrf_score": 0.003745318352059925,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 102,
            "quality_score": 35
          }
        },
        {
          "result_id": "d20253b11766adc2e0295ab1ba885e90",
          "position": 320,
          "page_position": 8,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.003745318352059925,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 116,
            "quality_score": 45
          }
        },
        {
          "result_id": "b5cf3c2a57a7a1db0bbd0a71a9456eb7",
          "position": 321,
          "page_position": 9,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34713379459775606,
            "rrf_score": 0.0037313432835820895,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 70,
            "quality_score": 35
          }
        },
        {
          "result_id": "d5e13144b34f3d7ebc6c4944cf57f844",
          "position": 322,
          "page_position": 10,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.0037313432835820895,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 317,
            "quality_score": 45
          }
        },
        {
          "result_id": "151aa64c6a8a830ad60e40c1571f94e7",
          "position": 323,
          "page_position": 11,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3472455533000486,
            "rrf_score": 0.0037174721189591076,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 94,
            "quality_score": 35
          }
        },
        {
          "result_id": "5f146c2f6b0de6c68e4e963394296661",
          "position": 324,
          "page_position": 12,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3473401640641385,
            "rrf_score": 0.003703703703703704,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 78,
            "quality_score": 35
          }
        },
        {
          "result_id": "e7d702a9a9c389721beecee5c80e5068",
          "position": 325,
          "page_position": 13,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.003703703703703704,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 72,
            "quality_score": 45
          }
        },
        {
          "result_id": "f156e80d7bee2aa2f1ad3dfaeee795fb",
          "position": 326,
          "page_position": 14,
          "retrieval_features": {
            "bm25_score": -7.185502529144287,
            "vector_score": 0,
            "rrf_score": 0.0036900369003690036,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 149,
            "quality_score": 45
          }
        },
        {
          "result_id": "7410f34c3135aebc3921507dba10d4ef",
          "position": 327,
          "page_position": 15,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34742943361822054,
            "rrf_score": 0.0036900369003690036,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": false,
            "salary_disclosed": true,
            "posted_age_days": 1275,
            "quality_score": 55
          }
        },
        {
          "result_id": "1e3fa6cf25306ee92b7ab4a9d7575b87",
          "position": 328,
          "page_position": 16,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3474441741506731,
            "rrf_score": 0.003676470588235294,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": true,
            "posted_age_days": 210,
            "quality_score": 55
          }
        },
        {
          "result_id": "0f9e1906f1aaaf4c39a0b10e176b0ea9",
          "position": 329,
          "page_position": 17,
          "retrieval_features": {
            "bm25_score": -6.943520545959473,
            "vector_score": 0,
            "rrf_score": 0.003676470588235294,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 84,
            "quality_score": 45
          }
        },
        {
          "result_id": "a0f8b23a6ba6bb8fd5796029736676c6",
          "position": 330,
          "page_position": 18,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34753201320576477,
            "rrf_score": 0.003663003663003663,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 75,
            "quality_score": 35
          }
        },
        {
          "result_id": "21c47244ffcbfcaba3b8a626b15f6115",
          "position": 331,
          "page_position": 19,
          "retrieval_features": {
            "bm25_score": -6.943520545959473,
            "vector_score": 0,
            "rrf_score": 0.003663003663003663,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": false,
            "salary_disclosed": false,
            "posted_age_days": 436,
            "quality_score": 45
          }
        },
        {
          "result_id": "6a6fbf83e5776a4f454e545465606547",
          "position": 332,
          "page_position": 20,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3476086258888198,
            "rrf_score": 0.0036496350364963502,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 71,
            "quality_score": 35
          }
        },
        {
          "result_id": "26b180f141b500b83aa3751c81e1d11b",
          "position": 333,
          "page_position": 21,
          "retrieval_features": {
            "bm25_score": -6.943520545959473,
            "vector_score": 0,
            "rrf_score": 0.0036496350364963502,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 102,
            "quality_score": 45
          }
        },
        {
          "result_id": "3dc25e14a8f973c555353d7b325351b3",
          "position": 334,
          "page_position": 22,
          "retrieval_features": {
            "bm25_score": -6.943520545959473,
            "vector_score": 0,
            "rrf_score": 0.0036363636363636364,
            "text_match_title": true,
            "text_match_employer": false,
            "role_match": false,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 72,
            "quality_score": 45
          }
        },
        {
          "result_id": "9478389ec219ad4374a646e3dc664cdb",
          "position": 335,
          "page_position": 23,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.34770454791730077,
            "rrf_score": 0.0036363636363636364,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 102,
            "quality_score": 35
          }
        },
        {
          "result_id": "03a048320090d6496cca34ac745b99bd",
          "position": 336,
          "page_position": 24,
          "retrieval_features": {
            "bm25_score": 0,
            "vector_score": 0.3477362783112349,
            "rrf_score": 0.0036231884057971015,
            "text_match_title": false,
            "text_match_employer": false,
            "role_match": true,
            "benefit_verified": true,
            "salary_disclosed": false,
            "posted_age_days": 70,
            "quality_score": 35
          }
        }
      ]
    },
    "context_signature": "0IltHqsBVgT4BbKCCp-lG-v7QJ68-4EaiwSN9wBlqP4",
    "event_token": "0IltHqsBVgT4BbKCCp-lG-v7QJ68-4EaiwSN9wBlqP4"
  }
}