{ "results": [ { "id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "title": "Retail Associate", "employer_name": "Infinite Machine", "employer_slug": "infinite-machine", "location_text": "New York, NY, 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": [ "a16z" ], "posted_at": "2026-04-13T18:17:01.542Z", "apply_url": "https://jobs.ashbyhq.com/infinite-machine/76bf8faa-bdaf-4edc-ba0d-ea9664d1f40d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Retail Associate New York, NY, United States Overview Infinite Machine is hiring a Retail Associate to lead vehicle sales in New York City. You will build relationships with high-value customers, close deals, and help shape how we grow. This is a frontline role for someone who knows how to sell premium products and is excited about redefining urban mobility. What You'll Do - Own and drive vehicle sales in NYC - Build relationships with new customers and convert interest into purchases - Lead product demos and test rides - Represent Infinite Machine at events and local activations - Work closely with marketing and leadership to align on sales goals - Track sales performance and share insights to improve the sales process - Help create a repeatable sales playbook to scale nationally You Bring - 2-5 years of experience in vehicle sales, luxury retail, or premium customer sales - Proven record of hitting or exceeding targets - Strong knowledge of the NYC market - Clear communicator with strong closing instincts - Comfortable in fast-moving environments - Passion for design, technology, and urban mobility About Infinite Machine Our mission at Infinite Machine is to build the best non-cars on earth. We design and manufacture premium electric vehicles that blend design with breakthrough hardware and software. With P1 and Olto , we are reimagining how people move through cities and laying the foundation for a broader ecosystem of vehicles, software, and services. We are hiring world-class engineers, designers, and operators to build a", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": 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" }, "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": "entry", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 9, "role_function": "retail", "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.79c6e594533bc54761", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Retail Associate New York, NY, United States Overview Infinite Machine is hiring a Retail Associate to lead vehicle sales in New York City. You will build relationships with high-value customers, close deals, and help shape how we grow. This is a frontline role for someone who knows how to sell premium products and is excited about redefining urban mobility. What You'll Do - Own and drive vehicle sales in NYC - Build relationships with new customers and convert interest into purchases - Lead product demos and test rides - Represent Infinite Machine at events and local activations - Work closely with marketing and leadership to align on sales goals - Track sales performance and share insights to improve the sales process - Help create a repeatable sales playbook to scale nationally You Bring - 2-5 years of experience in vehicle sales, luxury retail, or premium customer sales - Proven record of hitting or exceeding targets - Strong knowledge of the NYC market - Clear communicator with strong closing instincts - Comfortable in fast-moving environments - Passion for design, technology, and urban mobility About Infinite Machine Our mission at Infinite Machine is to build the best non-cars on earth. We design and manufacture premium electric vehicles that blend design with breakthrough hardware and software. With P1 and Olto , we are reimagining how people move through cities and laying the foundation for a broader ecosystem of vehicles, software, and services. We are hiring world-class engineers, designers, and operators to build a", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8a9f8fd5284fc0d9b34ef3c663bf8435:description:infinite", "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.f175788f0bcf8eca9d", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Retail Associate New York, NY, United States Overview Infinite Machine is hiring a Retail Associate to lead vehicle sales in New York City. You will build relationships with high-value customers, close deals, and help shape how we grow. This is a frontline role for someone who knows how to sell premium products and is excited about redefining urban mobility. What You'll Do - Own and drive vehicle sales in NYC - Build relationships with new customers and convert interest into purchases - Lead product demos and test rides - Represent Infinite Machine at events and local activations - Work closely with marketing and leadership to align on sales goals - Track sales performance and share insights to improve the sales process - Help create a repeatable sales playbook to scale nationally You Bring - 2-5 years of experience in vehicle sales, luxury retail, or premium customer sales - Proven record of hitting or exceeding targets - Strong knowledge of the NYC market - Clear communicator with strong closing instincts - Comfortable in fast-moving environments - Passion for design, technology, and urban mobility About Infinite Machine Our mission at Infinite Machine is to build the best non-cars on earth. We design and manufacture premium electric vehicles that blend design with breakthrough hardware and software. With P1 and Olto , we are reimagining how people move through cities and laying the foundation for a broader ecosystem of vehicles, software, and services. We are hiring world-class engineers, designers, and operators to build a", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8a9f8fd5284fc0d9b34ef3c663bf8435:description:machine", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.339675af09e1600a96", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8a9f8fd5284fc0d9b34ef3c663bf8435:employer:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.3d6a8ea14d62d90e38", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8a9f8fd5284fc0d9b34ef3c663bf8435:employer:machine", "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.semantic.employer_name.63a65c18367f85d8cb", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:81649dba641320964864af78", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4df7fc16681d53ed8f", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a5582bb66b63275ece", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.0fd2018e350c56256c", "query_id": "gq_d70e222980c74de92307", "job_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "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": "retail", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8a9f8fd5284fc0d9b34ef3c663bf8435:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/infinite-machine/76bf8faa-bdaf-4edc-ba0d-ea9664d1f40d", "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/infinite-machine/76bf8faa-bdaf-4edc-ba0d-ea9664d1f40d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "f9647dd27f6fb442aca9db875d6e686c", "title": "Creative Director", "employer_name": "Infinite Machine", "employer_slug": "infinite-machine", "location_text": "New York, NY, 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": [ "a16z" ], "posted_at": "2024-09-29T22:13:04.894Z", "apply_url": "https://jobs.ashbyhq.com/infinite-machine/0406519a-ab6a-4229-ba9b-f43049083d47", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Creative Director New York, NY, United States Overview Infinite Machine is looking for a Creative Director to help push its brand in ways we cannot imagine. You will shape the voice and visual language of Infinite Machine across all surfaces - graphics, campaigns, packaging, social media, retail, and everything in between. This role is for someone who wants to do daring, exceptional work - someone who gets excited about defining a generational vehicle brand, about pushing the envelope of visual storytelling, and creating iconic marketing. It's a role that will report directly to our founders. We will take risks, and we will empower you to push, and then push further. Responsibilities: - Move fluidly between big brand direction and tiny execution details. - Determine what stories we tell and shape how they look both for large campaigns and small social narratives. You will make commercials and long-form brand films that define how Infinite Machine enters culture. - Direct our in house DP and own the full visual tone of all video and photo. - Design graphics across every surface: product graphics, invitations, web, etc. - Design our retail presence: layout, material palette, lighting, sound, signage, and overall atmosphere. - Shape the look and feel of product launches, activations, and events. - Work directly with our industrial design team to align hardware aesthetics with brand identity. - Push our product photography style and maintain a consistent visual language across P1, Olto, and future vehicles. - Guide social creative so every post", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "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" }, "portfolio_required": { "field": "portfolio_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "portfolio_required" } }, "seniority": "director_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "design", "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.c51172c9419301bbed", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Creative Director New York, NY, United States Overview Infinite Machine is looking for a Creative Director to help push its brand in ways we cannot imagine. You will shape the voice and visual language of Infinite Machine across all surfaces - graphics, campaigns, packaging, social media, retail, and everything in between. This role is for someone who wants to do daring, exceptional work - someone who gets excited about defining a generational vehicle brand, about pushing the envelope of visual storytelling, and creating iconic marketing. It's a role that will report directly to our founders. We will take risks, and we will empower you to push, and then push further. Responsibilities: - Move fluidly between big brand direction and tiny execution details. - Determine what stories we tell and shape how they look both for large campaigns and small social narratives. You will make commercials and long-form brand films that define how Infinite Machine enters culture. - Direct our in house DP and own the full visual tone of all video and photo. - Design graphics across every surface: product graphics, invitations, web, etc. - Design our retail presence: layout, material palette, lighting, sound, signage, and overall atmosphere. - Shape the look and feel of product launches, activations, and events. - Work directly with our industrial design team to align hardware aesthetics with brand identity. - Push our product photography style and maintain a consistent visual language across P1, Olto, and future vehicles. - Guide social creative so every post", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:f9647dd27f6fb442aca9db875d6e686c:description:machine", "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.db1aa011c20b53541e", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Creative Director New York, NY, United States Overview Infinite Machine is looking for a Creative Director to help push its brand in ways we cannot imagine. You will shape the voice and visual language of Infinite Machine across all surfaces - graphics, campaigns, packaging, social media, retail, and everything in between. This role is for someone who wants to do daring, exceptional work - someone who gets excited about defining a generational vehicle brand, about pushing the envelope of visual storytelling, and creating iconic marketing. It's a role that will report directly to our founders. We will take risks, and we will empower you to push, and then push further. Responsibilities: - Move fluidly between big brand direction and tiny execution details. - Determine what stories we tell and shape how they look both for large campaigns and small social narratives. You will make commercials and long-form brand films that define how Infinite Machine enters culture. - Direct our in house DP and own the full visual tone of all video and photo. - Design graphics across every surface: product graphics, invitations, web, etc. - Design our retail presence: layout, material palette, lighting, sound, signage, and overall atmosphere. - Shape the look and feel of product launches, activations, and events. - Work directly with our industrial design team to align hardware aesthetics with brand identity. - Push our product photography style and maintain a consistent visual language across P1, Olto, and future vehicles. - Guide social creative so every post", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:f9647dd27f6fb442aca9db875d6e686c:description:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.32ac605aaa07994219", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:f9647dd27f6fb442aca9db875d6e686c:employer:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.95320cf25fa441dbe2", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:f9647dd27f6fb442aca9db875d6e686c:employer:machine", "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.semantic.employer_name.7dbd3d512710456fff", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:2f90bfe838394aaba1dd42c9", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.20032c01fef9dd9763", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.ad61a56e6cc884aeb3", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.2f4e4eed0ea673d068", "query_id": "gq_d70e222980c74de92307", "job_id": "f9647dd27f6fb442aca9db875d6e686c", "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": "design", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:f9647dd27f6fb442aca9db875d6e686c:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/infinite-machine/0406519a-ab6a-4229-ba9b-f43049083d47", "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/infinite-machine/0406519a-ab6a-4229-ba9b-f43049083d47", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "d92be948229a9d4191d4219d2d35bec3", "title": "Customer Operations Associate", "employer_name": "Infinite Machine", "employer_slug": "infinite-machine", "location_text": "New York, NY, 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": [ "a16z" ], "posted_at": "2026-05-21T17:23:55.315Z", "apply_url": "https://jobs.ashbyhq.com/infinite-machine/840bd929-34e0-45f0-b802-2e9519cec580", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Customer Operations Associate New York, NY, United States Overview Infinite Machine is hiring a Customer Operations Associate to own the post-purchase customer journey for P1, a plated electric motorcycle, and Olto, a Class 2 e-bike. This role sits within the Operations function and covers delivery logistics, vehicle registration support, light assembly and service, and customer issue resolution, working closely with the Marketing, Sales, and Service teams. The Customer Operations Associate is responsible for scheduling, tracking, and completing customer deliveries across store locations, performing regional deliveries by van, and ensuring vehicles are prepared and assembled correctly before handoff. It also owns customer communications, escalating to Service or Engineering as needed and working with those teams to deliver positive customer outcomes. This is a hands-on, in-person operations role, not a contact-center, desk, or Tier 1 support queue position . Customer communication is one component of the work rather than its primary focus. The role is on-site and field-based, working closely with a small operations team out of our headquarters in Long Island City. Responsibilities - Delivery operations. Schedule, track, stage, and dispatch customer deliveries across our store locations. Personally perform regional deliveries by van. Own the delivery experience as the customer's first physical impression of the brand. - Customer communications. Monitor inbound channels and own Tier 1 resolution for existing customers. Draft and send clear group and individual communications, pick up the phone when a thread is not working, and partner with Service and Engineering to close out anything beyond Tier 1", "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" } }, "seniority": "entry", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 0, "years_experience_max": 4, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": 10, "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.bf8234c787af6b006b", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Customer Operations Associate New York, NY, United States Overview Infinite Machine is hiring a Customer Operations Associate to own the post-purchase customer journey for P1, a plated electric motorcycle, and Olto, a Class 2 e-bike. This role sits within the Operations function and covers delivery logistics, vehicle registration support, light assembly and service, and customer issue resolution, working closely with the Marketing, Sales, and Service teams. The Customer Operations Associate is responsible for scheduling, tracking, and completing customer deliveries across store locations, performing regional deliveries by van, and ensuring vehicles are prepared and assembled correctly before handoff. It also owns customer communications, escalating to Service or Engineering as needed and working with those teams to deliver positive customer outcomes. This is a hands-on, in-person operations role, not a contact-center, desk, or Tier 1 support queue position . Customer communication is one component of the work rather than its primary focus. The role is on-site and field-based, working closely with a small operations team out of our headquarters in Long Island City. Responsibilities - Delivery operations. Schedule, track, stage, and dispatch customer deliveries across our store locations. Personally perform regional deliveries by van. Own the delivery experience as the customer's first physical impression of the brand. - Customer communications. Monitor inbound channels and own Tier 1 resolution for existing customers. Draft and send clear group and individual communications, pick up the phone when a thread is not working, and partner with Service and Engineering to close out anything beyond Tier 1", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d92be948229a9d4191d4219d2d35bec3:description:machine", "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.cef6a11986ce700910", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Customer Operations Associate New York, NY, United States Overview Infinite Machine is hiring a Customer Operations Associate to own the post-purchase customer journey for P1, a plated electric motorcycle, and Olto, a Class 2 e-bike. This role sits within the Operations function and covers delivery logistics, vehicle registration support, light assembly and service, and customer issue resolution, working closely with the Marketing, Sales, and Service teams. The Customer Operations Associate is responsible for scheduling, tracking, and completing customer deliveries across store locations, performing regional deliveries by van, and ensuring vehicles are prepared and assembled correctly before handoff. It also owns customer communications, escalating to Service or Engineering as needed and working with those teams to deliver positive customer outcomes. This is a hands-on, in-person operations role, not a contact-center, desk, or Tier 1 support queue position . Customer communication is one component of the work rather than its primary focus. The role is on-site and field-based, working closely with a small operations team out of our headquarters in Long Island City. Responsibilities - Delivery operations. Schedule, track, stage, and dispatch customer deliveries across our store locations. Personally perform regional deliveries by van. Own the delivery experience as the customer's first physical impression of the brand. - Customer communications. Monitor inbound channels and own Tier 1 resolution for existing customers. Draft and send clear group and individual communications, pick up the phone when a thread is not working, and partner with Service and Engineering to close out anything beyond Tier 1", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d92be948229a9d4191d4219d2d35bec3:description:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.948eb8d137639370d2", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d92be948229a9d4191d4219d2d35bec3:employer:machine", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.d7dac856108448c9fd", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d92be948229a9d4191d4219d2d35bec3:employer:infinite", "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.semantic.employer_name.478b76ae9e077465e4", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:e5e796d9e552387f6554dae2", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.63fe91fe8aa02d3e70", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.8078a2a4d7f5344619", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Employer: \"machine\"", "tooltip": "Employer contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite Machine", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c53ebd59ba2786c838", "query_id": "gq_d70e222980c74de92307", "job_id": "d92be948229a9d4191d4219d2d35bec3", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "operations", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d92be948229a9d4191d4219d2d35bec3:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/infinite-machine/840bd929-34e0-45f0-b802-2e9519cec580", "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/infinite-machine/840bd929-34e0-45f0-b802-2e9519cec580", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "642d49047e2218f11db6b8281e46cc1c", "title": "Founding Engineer", "employer_name": "Infinite", "employer_slug": "infinite", "location_text": "San Francisco | OnSite", "country": "US", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/infinite/d882cb98-0cea-429c-97a0-8b05f56768ae", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding Engineer San Francisco | OnSite COMPANY OVERVIEW Infinite is a stablecoin payment processor. We offer businesses turnkey APIs and SDKs to instantly move money anywhere in the world at a fraction of the cost of traditional solutions. The founding team previously built and scaled products at financial services category leaders Coinbase https://coinbase.com and Sardine https://sardine.ai. THE OPPORTUNITY As our Founding Engineer, you will define, build, and maintain the technical foundation of our platform. You will join us in-person in a fast-paced, high-ownership environment where you will take ownership of everything, from architecture and implementation to production reliability for mission-critical services. You will partner directly with founders and early customers to translate real-world requirements into robust, high-quality products. KEY RESPONSIBILITIES 1. Full Stack & End-to-End - Design, implement, and operate complete services and user-facing features, from requirements gathering through production support 2. System Design & Architecture - Develop highly available, event-driven systems for ledgering, compliance, and risk that scale with transaction volume while maintaining zero downtime 3. Implementation Engineering - Embed with customers, collect feedback, and iterate rapidly to ensure our roadmap aligns with user needs 4. Technical Decision-Making - Balance speed and long-term scalability, selecting appropriate technologies (Next.js/TypeScript, C#, Go, Python, modern cloud infrastructure) for each problem domain REQUIRED SKILLS & EXPERIENCE - 2-5+ years of professional software engineering, including the delivery of 0-to-1 products and scaling them in production - Proficiency in at least two of: Next.js/TypeScript, C#, Go, Python - Hands-on expertise with asynchronous and event-driven arc", "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" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.29de3d2121df6a6f6d", "query_id": "gq_d70e222980c74de92307", "job_id": "642d49047e2218f11db6b8281e46cc1c", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:070cfcaed3aabc37f1728979", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.fecc6bf6326a516b19", "query_id": "gq_d70e222980c74de92307", "job_id": "642d49047e2218f11db6b8281e46cc1c", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.52f366bab6b091f22c", "query_id": "gq_d70e222980c74de92307", "job_id": "642d49047e2218f11db6b8281e46cc1c", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:642d49047e2218f11db6b8281e46cc1c:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/infinite/d882cb98-0cea-429c-97a0-8b05f56768ae", "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/infinite/d882cb98-0cea-429c-97a0-8b05f56768ae", "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/infinite/d882cb98-0cea-429c-97a0-8b05f56768ae", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6f7bfb60299046c0d68321ef39b68dc1", "title": "Infinite Kitchen Operations Specialist", "employer_name": "Sweetgreen INC", "employer_slug": "sweetgreen", "location_text": "Los Angeles, CA", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 65000, "salary_max": 92000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base_plus_commission", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 65000, "base_salary_max": 92000, "salary_disclosed": true, "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": true, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Infinite Kitchen Operations Specialist Los Angeles, CA We're looking for an operationally-minded Infinite Kitchen (IK) Operations Specialist to support Sweetgreen's growing Infinite Kitchen (IK) portfolio. This role sits at the intersection of IK technology, restaurant operations, and cross-functional Support Center teams. The ideal candidate is equally comfortable walking a restaurant with a GM and presenting a recommendation to senior leadership. This is a role for someone who can earn operator trust, push back on assumptions, and translate field reality into decisions that get made at the Support Center. You're the person who ensures adoption of processes and new initiatives at IK's and that the voice of operators and guests informs the future of IK's. You'll partner closely with Operations, Facilities, Technology, and People teams to drive operational improvements across the IK fleet, lead in-restaurant pilots, and provide field coordination for new IK openings. This role is based in our Los Angeles Support Center, with 15-30% travel to IK restaurants. KEY RESPONSIBILITIES Infinite Kitchen (IK) Operations & Testing Serve as the primary IK field voice, representing operator perspectives to Technology, People, Facilities, and Operations leadership. Own and refine feedback loop between support team and IK Operators Inform test and launch decisions by ensuring cross-functional partners account for operator capacity, training implications, and execution realities before initiatives go live. When something won't work in IK operations, you're the person who says so and helps shape the fix. Own a portfolio of operational improvement projects across the IK fleet, including but not limited", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1477815/000162828026012520/sg-20251228.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1477815/000162828026012520/sg-20251228.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": "operations", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Retail", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": 30, "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.10a1fdaed4d898dba5", "query_id": "gq_d70e222980c74de92307", "job_id": "6f7bfb60299046c0d68321ef39b68dc1", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Infinite Kitchen Operations Specialist Los Angeles, CA We're looking for an operationally-minded Infinite Kitchen (IK) Operations Specialist to support Sweetgreen's growing Infinite Kitchen (IK) portfolio. This role sits at the intersection of IK technology, restaurant operations, and cross-functional Support Center teams. The ideal candidate is equally comfortable walking a restaurant with a GM and presenting a recommendation to senior leadership. This is a role for someone who can earn operator trust, push back on assumptions, and translate field reality into decisions that get made at the Support Center. You're the person who ensures adoption of processes and new initiatives at IK's and that the voice of operators and guests informs the future of IK's. You'll partner closely with Operations, Facilities, Technology, and People teams to drive operational improvements across the IK fleet, lead in-restaurant pilots, and provide field coordination for new IK openings. This role is based in our Los Angeles Support Center, with 15-30% travel to IK restaurants. KEY RESPONSIBILITIES Infinite Kitchen (IK) Operations & Testing Serve as the primary IK field voice, representing operator perspectives to Technology, People, Facilities, and Operations leadership. Own and refine feedback loop between support team and IK Operators Inform test and launch decisions by ensuring cross-functional partners account for operator capacity, training implications, and execution realities before initiatives go live. When something won't work in IK operations, you're the person who says so and helps shape the fix. Own a portfolio of operational improvement projects across the IK fleet, including but not limited", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6f7bfb60299046c0d68321ef39b68dc1:description:infinite", "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.ad613499cdcc7dbcc7", "query_id": "gq_d70e222980c74de92307", "job_id": "6f7bfb60299046c0d68321ef39b68dc1", "signal_type": "query_match", "display_text": "Title: \"infinite\"", "tooltip": "Title matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Infinite Kitchen Operations Specialist", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6f7bfb60299046c0d68321ef39b68dc1:title:infinite", "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.semantic.title.2f82499ca799737379", "query_id": "gq_d70e222980c74de92307", "job_id": "6f7bfb60299046c0d68321ef39b68dc1", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Infinite Kitchen Operations Specialist", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:1018bd3267fe73c086c18314", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.0805320e01387dca98", "query_id": "gq_d70e222980c74de92307", "job_id": "6f7bfb60299046c0d68321ef39b68dc1", "signal_type": "query_match", "display_text": "Title: \"infinite\"", "tooltip": "Title contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Infinite Kitchen Operations Specialist", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.e19892ee79984912c5", "query_id": "gq_d70e222980c74de92307", "job_id": "6f7bfb60299046c0d68321ef39b68dc1", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "operations", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6f7bfb60299046c0d68321ef39b68dc1:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1477815/000162828026012520/sg-20251228.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1477815/000162828026012520/sg-20251228.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "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://careers.sweetgreen.com/jobs/7951021?gh_jid=7951021", "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": "8d302b50361fea98136c627ca9a978e0", "title": "Founding GTM Lead", "employer_name": "Infinite", "employer_slug": "infinite", "location_text": "Presidio | OnSite", "country": "unknown", "employment_type": "contract", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://jobs.ashbyhq.com/infinite/6837e17c-522f-4784-a169-10744c0774c2", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding GTM Lead Presidio | OnSite Infinite is a stablecoin payment processor. We offer businesses turnkey APIs and SDKs to instantly move money anywhere in the world at a fraction of the cost of traditional solutions. WHAT YOU'LL DO - Full-cycle revenue ownership: Source, qualify, demo, negotiate, and close multi-million dollar B2B contracts across our four core ICP segments: cross-border PSPs and MTOs, neobanks and digital banks, fintech platforms, and stablecoin infrastructure and FX. You complement and amplify founder-led sales. Founders stay on the calls. You own the cadence, the close, and the commercial. - Activation, contracted to live: Own the path from signed deal to first $1M in volume processed. Most of Infinite's ACV unlocks at activation, not at signature, so closing the loop across contract execution, technical integration, compliance onboarding, and customer ramp is where this role lives. Pull in Erebor, our compliance partners, and engineering when the deal calls for it. - Outbound engine and GTM systems: Build the outbound motion with Clay, HubSpot, and Unify against signal-rich lists in each ICP segment. Stand up the CRM, pipeline tracking, and reporting infrastructure. Own inbound sequencing from content-driven awareness through demo, and codify the qualification rubric so the next seller does not have to relearn it. - Commercial and contract delivery: Build the pricing playbook spanning transfer fees, FX spread, compliance, and platform fees. Lead commercial negotiation. Own SOWs, SLAs, and regulated contract structures end to end alongside legal, compliance, and our sponsor bank partner. - Product-led growth", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "sales", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "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.332fcfc38664b83f6b", "query_id": "gq_d70e222980c74de92307", "job_id": "8d302b50361fea98136c627ca9a978e0", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding GTM Lead Presidio | OnSite Infinite is a stablecoin payment processor. We offer businesses turnkey APIs and SDKs to instantly move money anywhere in the world at a fraction of the cost of traditional solutions. WHAT YOU'LL DO - Full-cycle revenue ownership: Source, qualify, demo, negotiate, and close multi-million dollar B2B contracts across our four core ICP segments: cross-border PSPs and MTOs, neobanks and digital banks, fintech platforms, and stablecoin infrastructure and FX. You complement and amplify founder-led sales. Founders stay on the calls. You own the cadence, the close, and the commercial. - Activation, contracted to live: Own the path from signed deal to first $1M in volume processed. Most of Infinite's ACV unlocks at activation, not at signature, so closing the loop across contract execution, technical integration, compliance onboarding, and customer ramp is where this role lives. Pull in Erebor, our compliance partners, and engineering when the deal calls for it. - Outbound engine and GTM systems: Build the outbound motion with Clay, HubSpot, and Unify against signal-rich lists in each ICP segment. Stand up the CRM, pipeline tracking, and reporting infrastructure. Own inbound sequencing from content-driven awareness through demo, and codify the qualification rubric so the next seller does not have to relearn it. - Commercial and contract delivery: Build the pricing playbook spanning transfer fees, FX spread, compliance, and platform fees. Lead commercial negotiation. Own SOWs, SLAs, and regulated contract structures end to end alongside legal, compliance, and our sponsor bank partner. - Product-led growth", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8d302b50361fea98136c627ca9a978e0:description:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.65f6db41600e4d6c91", "query_id": "gq_d70e222980c74de92307", "job_id": "8d302b50361fea98136c627ca9a978e0", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8d302b50361fea98136c627ca9a978e0:employer:infinite", "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.semantic.employer_name.9896c33d2157935841", "query_id": "gq_d70e222980c74de92307", "job_id": "8d302b50361fea98136c627ca9a978e0", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:c8512ef6d81c69e5d2a11a9e", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e7cf9e14475af74270", "query_id": "gq_d70e222980c74de92307", "job_id": "8d302b50361fea98136c627ca9a978e0", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.60120d6d741356119f", "query_id": "gq_d70e222980c74de92307", "job_id": "8d302b50361fea98136c627ca9a978e0", "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": "sales", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8d302b50361fea98136c627ca9a978e0:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/infinite/6837e17c-522f-4784-a169-10744c0774c2", "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/infinite/6837e17c-522f-4784-a169-10744c0774c2", "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/infinite/6837e17c-522f-4784-a169-10744c0774c2", "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/infinite/6837e17c-522f-4784-a169-10744c0774c2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "8bb9a6209b485049dae509abceb27989", "title": "Senior AML Analyst", "employer_name": "Infinite", "employer_slug": "infinite", "location_text": "Presidio | OnSite", "country": "unknown", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/infinite/978a89e3-aa6e-401a-bf89-3c425234653b", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AML Analyst Presidio | OnSite OVERVIEW As a Senior AML Analyst, you'll work directly alongside the CCO to operate the AML/BSA compliance program day-to-day. This isn't a queue-clearing role at a large bank - you'll own the full transaction monitoring and investigation lifecycle for a stablecoin payment processor handling cross-border B2B flows. Concretely, that means you'll be monitoring USD stablecoin settlement flows between US banks and international endpoints, analyzing on-chain transaction patterns through a blockchain analytics platform, investigating alerts that span fiat on-ramps, stablecoin transfers, and fiat off-ramps across multiple corridors, and preparing UARs for our sponsor bank partner. As Infinite obtains MTLs, you'll help transition to filing SARs directly with FinCEN. You'll also have direct input into how we build: monitoring rule design, investigation playbooks, risk-scoring thresholds, and operational processes that will scale with the business. WHAT YOU'LL DO Transaction Monitoring & Investigations Own daily alert triage across all supported stablecoin networks. Monitor for risk patterns specific to Infinite's verticals: structuring across payout batches, round-dollar anomalies, just-below-threshold transfers, and unusual geographic velocity. Analyze volume-based triggers against expected activity profiles - flag sudden spikes, dormant account reactivation, and velocity rule exceptions. Conduct behavioral analysis by vertical, comparing customers against peer group patterns. Execute the full investigation lifecycle: alert review, customer file review, on-chain and fiat transaction analysis, EDD when triggered, documentation, and escalation or closure. Suspicious Activity Reporting Draft UARs for CCO review with the specificity our sponsor bank requires: transaction timelines,", "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" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.698f990305e2a3abfc", "query_id": "gq_d70e222980c74de92307", "job_id": "8bb9a6209b485049dae509abceb27989", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior AML Analyst Presidio | OnSite OVERVIEW As a Senior AML Analyst, you'll work directly alongside the CCO to operate the AML/BSA compliance program day-to-day. This isn't a queue-clearing role at a large bank - you'll own the full transaction monitoring and investigation lifecycle for a stablecoin payment processor handling cross-border B2B flows. Concretely, that means you'll be monitoring USD stablecoin settlement flows between US banks and international endpoints, analyzing on-chain transaction patterns through a blockchain analytics platform, investigating alerts that span fiat on-ramps, stablecoin transfers, and fiat off-ramps across multiple corridors, and preparing UARs for our sponsor bank partner. As Infinite obtains MTLs, you'll help transition to filing SARs directly with FinCEN. You'll also have direct input into how we build: monitoring rule design, investigation playbooks, risk-scoring thresholds, and operational processes that will scale with the business. WHAT YOU'LL DO Transaction Monitoring & Investigations Own daily alert triage across all supported stablecoin networks. Monitor for risk patterns specific to Infinite's verticals: structuring across payout batches, round-dollar anomalies, just-below-threshold transfers, and unusual geographic velocity. Analyze volume-based triggers against expected activity profiles - flag sudden spikes, dormant account reactivation, and velocity rule exceptions. Conduct behavioral analysis by vertical, comparing customers against peer group patterns. Execute the full investigation lifecycle: alert review, customer file review, on-chain and fiat transaction analysis, EDD when triggered, documentation, and escalation or closure. Suspicious Activity Reporting Draft UARs for CCO review with the specificity our sponsor bank requires: transaction timelines,", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8bb9a6209b485049dae509abceb27989:description:infinite", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.32168e5b990c485c8d", "query_id": "gq_d70e222980c74de92307", "job_id": "8bb9a6209b485049dae509abceb27989", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:8bb9a6209b485049dae509abceb27989:employer:infinite", "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.semantic.employer_name.a107538d02dc17113c", "query_id": "gq_d70e222980c74de92307", "job_id": "8bb9a6209b485049dae509abceb27989", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:ea92788e31d29abce0f71b96", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.debdeab3e0d814fe1e", "query_id": "gq_d70e222980c74de92307", "job_id": "8bb9a6209b485049dae509abceb27989", "signal_type": "query_match", "display_text": "Employer: \"infinite\"", "tooltip": "Employer contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Infinite", "matched_input": "infinite", "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/infinite/978a89e3-aa6e-401a-bf89-3c425234653b", "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/infinite/978a89e3-aa6e-401a-bf89-3c425234653b", "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/infinite/978a89e3-aa6e-401a-bf89-3c425234653b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6330ade0d4f894a03896bfa712703661", "title": "Machine Setup", "employer_name": "Regal Rexnord", "employer_slug": "regal-rexnord", "location_text": "New Hartford, Connecticut, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://regalrexnord.wd1.myworkdayjobs.com/Careers/job/New-Hartford-Connecticut-United-States/Machine-Setup_R26_02301", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Setup New Hartford, Connecticut, United States 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/82811/000008281126000054/rbc-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/82811/000008281126000054/rbc-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": "other", "role_function_source": "unknown", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.84cbf82301b4713eca", "query_id": "gq_d70e222980c74de92307", "job_id": "6330ade0d4f894a03896bfa712703661", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Machine Setup", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:1a421ac49f8445e0b8aaa847", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.ef7f7152a2ef0631f8", "query_id": "gq_d70e222980c74de92307", "job_id": "6330ade0d4f894a03896bfa712703661", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Setup", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.0a6129d53a3d4fc31a", "query_id": "gq_d70e222980c74de92307", "job_id": "6330ade0d4f894a03896bfa712703661", "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": "other", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6330ade0d4f894a03896bfa712703661: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/82811/000008281126000054/rbc-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/82811/000008281126000054/rbc-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://regalrexnord.wd1.myworkdayjobs.com/Careers/job/New-Hartford-Connecticut-United-States/Machine-Setup_R26_02301", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null } } }, { "id": "575378268580284e7662d189550be993", "title": "Machine Operator", "employer_name": "STMicroelectronics", "employer_slug": "stmicroelectronics", "location_text": "Hal Kirkop, Malta", "country": "MT", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://stmicroelectronics.eightfold.ai/careers/job/563637172115546", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Operator Hal Kirkop, Malta", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "operations", "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.title.52b2cf4c3eb0572015", "query_id": "gq_d70e222980c74de92307", "job_id": "575378268580284e7662d189550be993", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Machine Operator", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:618c9f60afd7812e370c38f5", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.7466cbb8bfc80d0f35", "query_id": "gq_d70e222980c74de92307", "job_id": "575378268580284e7662d189550be993", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Operator", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.66036ca6c7772c51a3", "query_id": "gq_d70e222980c74de92307", "job_id": "575378268580284e7662d189550be993", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "operations", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:575378268580284e7662d189550be993:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637172115546", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://stmicroelectronics.eightfold.ai/careers/job/563637172115546", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "09a13e8db232dfa8d4e0a147fb63bd92", "title": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "employer_name": "Howmet Aerospace", "employer_slug": "howmet-aerospace", "location_text": "Fullerton, 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": 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": "2026-06-03T00:00:00.000Z", "apply_url": "https://fa-exty-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/requisitions/job/117483", "apply_url_verified": false, "ats": "oracle_recruiting_cloud", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift Fullerton, CA, United States Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "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/4281/000000428126000012/hwm-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/4281/000000428126000012/hwm-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": "trades", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Defense", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2f113450e2fe270a04", "query_id": "gq_d70e222980c74de92307", "job_id": "09a13e8db232dfa8d4e0a147fb63bd92", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift Fullerton, CA, United States Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:09a13e8db232dfa8d4e0a147fb63bd92:description:machine", "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.06eed415963f1effdf", "query_id": "gq_d70e222980c74de92307", "job_id": "09a13e8db232dfa8d4e0a147fb63bd92", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:09a13e8db232dfa8d4e0a147fb63bd92:title:machine", "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.semantic.title.7e531831842e2ce4bf", "query_id": "gq_d70e222980c74de92307", "job_id": "09a13e8db232dfa8d4e0a147fb63bd92", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:0ecc9785fdbc2fe04f86c496", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.756f06c13a94f8be4e", "query_id": "gq_d70e222980c74de92307", "job_id": "09a13e8db232dfa8d4e0a147fb63bd92", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machining Tech V, Multi Spindle Screw Machine- 2nd Shift", "matched_input": "machine", "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/4281/000000428126000012/hwm-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/4281/000000428126000012/hwm-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://fa-exty-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/requisitions/job/117483", "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://fa-exty-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/requisitions/job/117483", "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": "771f64bb391f17ea2944f692ff793fcd", "title": "Machine Learning: Whole-Body Control", "employer_name": "The Bot Company", "employer_slug": "the-bot", "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" ], "posted_at": "2026-02-25T22:54:21.091Z", "apply_url": "https://jobs.ashbyhq.com/thebotcompany/69c93a4a-161a-49c9-89bc-4c3e0c4716e6", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning: Whole-Body Control San Francisco The Bot Company We're building a helpful robot for every home. We're a small team of engineers, designers, and operators based in San Francisco. Our team comes from Tesla, Cruise, OpenAI, Google, Pixar, and many other great companies. In the past we've shipped to hundreds of millions of users and know what it takes to build amazing products and experiences. Our team is deliberately lean to promote rapid decision making and do away with bureaucracy and hierarchy. Everyone is an IC and is empowered with massive scope, radical ownership, and direct responsibility. We work across the stack with a culture built for rapid iteration and fast execution. What we look for in all candidates All roles at The Bot Company demand extreme sharpness and the ability to move fast in high-intensity environments. Throughout the process, we expect candidates to demonstrate: - Exceptional mental acuity: you think quickly, learn instantly, and reason across unfamiliar domains. - Engineering curiosity: you naturally dig into how systems work, even outside your specialty. - High performance mindset: you move fast, handle ambiguity, and excel when the environment is demanding. Machine Learning: Whole-Body Control We are building high-performance whole-body controllers that produce robust, agile motion and manipulation in the real world. You will train low-level control policies in simulation and own the stack from environment design to large-scale training and sim-to-real deployment. What You'll Do - Train whole-body policies for locomotion, manipulation, and coordinated motion. - Build scalable simulation environments", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "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.semantic.title.26df7434a12c7948e1", "query_id": "gq_d70e222980c74de92307", "job_id": "771f64bb391f17ea2944f692ff793fcd", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Machine Learning: Whole-Body Control", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:1a550c37d33ce4381c6f8f5c", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.7fbd0afa89c3a8bbf8", "query_id": "gq_d70e222980c74de92307", "job_id": "771f64bb391f17ea2944f692ff793fcd", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Learning: Whole-Body Control", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.3e03e167f5902bac26", "query_id": "gq_d70e222980c74de92307", "job_id": "771f64bb391f17ea2944f692ff793fcd", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:771f64bb391f17ea2944f692ff793fcd:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/thebotcompany/69c93a4a-161a-49c9-89bc-4c3e0c4716e6", "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/thebotcompany/69c93a4a-161a-49c9-89bc-4c3e0c4716e6", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "41c90c40d04442fc7d6740254dc0da6f", "title": "Machine Learning Engineer: Evaluation", "employer_name": "Bedrock Robotics", "employer_slug": "bedrock-robotics", "location_text": "San Francisco, CA, San Francisco, California, United States, New York, NY", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": true, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-01-31T03:47:45.924Z", "apply_url": "https://jobs.ashbyhq.com/bedrock-robotics/5c2c834d-61f1-4ec9-812b-8665a9f5024d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Engineer: Evaluation San Francisco, CA, San Francisco, California, United States, New York, NY Join the team bringing advanced autonomy to the built world At Bedrock, we're moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We're a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We're looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "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" }, "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": 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.b2a9c156bbe07eadf6", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Engineer: Evaluation San Francisco, CA, San Francisco, California, United States, New York, NY Join the team bringing advanced autonomy to the built world At Bedrock, we're moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We're a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We're looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:41c90c40d04442fc7d6740254dc0da6f:description:machine", "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.f16dde832b4a3cbe46", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Engineer: Evaluation San Francisco, CA, San Francisco, California, United States, New York, NY Join the team bringing advanced autonomy to the built world At Bedrock, we're moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We're a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We're looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:41c90c40d04442fc7d6740254dc0da6f:description:infinite", "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.ee92591f74d0d6da67", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Machine Learning Engineer: Evaluation", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:41c90c40d04442fc7d6740254dc0da6f:title:machine", "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.semantic.description_excerpt.b637692e351a299032", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Engineer: Evaluation San Francisco, CA, San Francisco, California, United States, New York, NY Join the team bringing advanced autonomy to the built world At Bedrock, we're moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We're a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We're looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:0b98aae0c64606e9d2f56433", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d770588442657cfcc0", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Machine Learning Engineer: Evaluation San Francisco, CA, San Francisco, California, United States, New York, NY Join the team bringing advanced autonomy to the built world At Bedrock, we're moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We're a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We're looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.79d9ab6035a9a736fb", "query_id": "gq_d70e222980c74de92307", "job_id": "41c90c40d04442fc7d6740254dc0da6f", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Learning Engineer: Evaluation", "matched_input": "machine", "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/bedrock-robotics/5c2c834d-61f1-4ec9-812b-8665a9f5024d", "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/bedrock-robotics/5c2c834d-61f1-4ec9-812b-8665a9f5024d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "title": "CNC Machine Operator - All Shifts", "employer_name": "SendCutSend", "employer_slug": "sendcutsend", "location_text": "Reno, Nevada - CNC Machining", "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": [], "posted_at": "2026-05-21T18:12:35.000Z", "apply_url": "https://recruiting.paylocity.com/Recruiting/Jobs/Details/4191199", "apply_url_verified": false, "ats": "paylocity", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "CNC Machine Operator - All Shifts Reno, Nevada - CNC Machining CNC Machine Operator - All Shifts", "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" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "operations", "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.query.description_excerpt.3c905a5671b6a0722e", "query_id": "gq_d70e222980c74de92307", "job_id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "CNC Machine Operator - All Shifts Reno, Nevada - CNC Machining CNC Machine Operator - All Shifts", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:b31b972ed07e4e83e4fa38a0ac60b6fb:description:machine", "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.d0cb6685d178df39b0", "query_id": "gq_d70e222980c74de92307", "job_id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "CNC Machine Operator - All Shifts", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:b31b972ed07e4e83e4fa38a0ac60b6fb:title:machine", "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.semantic.title.2a07bcb3a1ab5647ed", "query_id": "gq_d70e222980c74de92307", "job_id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "CNC Machine Operator - All Shifts", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:a6107b8d55e5c4ee69a1bbc1", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.211c7a90128e3f33bf", "query_id": "gq_d70e222980c74de92307", "job_id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "CNC Machine Operator - All Shifts", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://recruiting.paylocity.com/Recruiting/Jobs/Details/4191199", "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://recruiting.paylocity.com/Recruiting/Jobs/Details/4191199", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "d7422cc37539c48db779d56be8a5d8c4", "title": "Machine Learning Infrastructure Engineer", "employer_name": "Character.AI", "employer_slug": "character-ai", "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", "a16z" ], "posted_at": "2025-04-24T17:17:46.443Z", "apply_url": "https://jobs.ashbyhq.com/character/13006848-6a69-4467-9274-5d54e80b965d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Machine Learning Infrastructure Engineer Redwood City, CA, Redwood City, California, United States About the role We're looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities : - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues and hardware failures - Monitor deployments, manage experiments, and generally support our research - Maximize GPU allocation and utilization for both serving and training Requirements: - 4+ years of experience supporting the infrastructure within an ML environment - Experience in developing tools used to diagnose ML infrastructure problems and failures - Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage) - Experience working with GPUs Nice to have - Experience with large GPU clusters and high-performance computing/networking - Experience with supporting large language model training - Experience with ML frameworks like Pytorch/TensorFlow/JAX - Experience with GPU kernel development About Character.AI Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year-a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!", "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" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 4, "years_experience_max": 8, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.541fab24fed379683f", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Infrastructure Engineer Redwood City, CA, Redwood City, California, United States About the role We're looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities : - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues and hardware failures - Monitor deployments, manage experiments, and generally support our research - Maximize GPU allocation and utilization for both serving and training Requirements: - 4+ years of experience supporting the infrastructure within an ML environment - Experience in developing tools used to diagnose ML infrastructure problems and failures - Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage) - Experience working with GPUs Nice to have - Experience with large GPU clusters and high-performance computing/networking - Experience with supporting large language model training - Experience with ML frameworks like Pytorch/TensorFlow/JAX - Experience with GPU kernel development About Character.AI Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year-a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d7422cc37539c48db779d56be8a5d8c4:description:infinite", "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.c98f88dda35b65a5fe", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Infrastructure Engineer Redwood City, CA, Redwood City, California, United States About the role We're looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities : - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues and hardware failures - Monitor deployments, manage experiments, and generally support our research - Maximize GPU allocation and utilization for both serving and training Requirements: - 4+ years of experience supporting the infrastructure within an ML environment - Experience in developing tools used to diagnose ML infrastructure problems and failures - Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage) - Experience working with GPUs Nice to have - Experience with large GPU clusters and high-performance computing/networking - Experience with supporting large language model training - Experience with ML frameworks like Pytorch/TensorFlow/JAX - Experience with GPU kernel development About Character.AI Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year-a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d7422cc37539c48db779d56be8a5d8c4:description:machine", "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.53f345c34e30175796", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Machine Learning Infrastructure Engineer", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d7422cc37539c48db779d56be8a5d8c4:title:machine", "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.semantic.description_excerpt.8effb8a2c21e9b6e86", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Infrastructure Engineer Redwood City, CA, Redwood City, California, United States About the role We're looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities : - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues and hardware failures - Monitor deployments, manage experiments, and generally support our research - Maximize GPU allocation and utilization for both serving and training Requirements: - 4+ years of experience supporting the infrastructure within an ML environment - Experience in developing tools used to diagnose ML infrastructure problems and failures - Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage) - Experience working with GPUs Nice to have - Experience with large GPU clusters and high-performance computing/networking - Experience with supporting large language model training - Experience with ML frameworks like Pytorch/TensorFlow/JAX - Experience with GPU kernel development About Character.AI Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year-a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:108095ec1b9f47208d8f4ebd", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2c78bd941f3cf56341", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Machine Learning Infrastructure Engineer Redwood City, CA, Redwood City, California, United States About the role We're looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities : - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues and hardware failures - Monitor deployments, manage experiments, and generally support our research - Maximize GPU allocation and utilization for both serving and training Requirements: - 4+ years of experience supporting the infrastructure within an ML environment - Experience in developing tools used to diagnose ML infrastructure problems and failures - Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage) - Experience working with GPUs Nice to have - Experience with large GPU clusters and high-performance computing/networking - Experience with supporting large language model training - Experience with ML frameworks like Pytorch/TensorFlow/JAX - Experience with GPU kernel development About Character.AI Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year-a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.eb6047fe55c9bb880f", "query_id": "gq_d70e222980c74de92307", "job_id": "d7422cc37539c48db779d56be8a5d8c4", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Learning Infrastructure Engineer", "matched_input": "machine", "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/character/13006848-6a69-4467-9274-5d54e80b965d", "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/character/13006848-6a69-4467-9274-5d54e80b965d", "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/character/13006848-6a69-4467-9274-5d54e80b965d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "2d33b49d567d7e8bc84eff55718eca99", "title": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning", "employer_name": "Viasat INC", "employer_slug": "viasat", "location_text": "Carlsbad, California", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 198500, "salary_max": 313000, "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": 198500, "base_salary_max": 313000, "salary_disclosed": true, "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": "2026-04-20T17:56:00.000Z", "apply_url": "https://careers-viasat.icims.com/jobs/5776/login", "apply_url_verified": true, "ats": "icims", "url_last_checked_alive": "2026-08-17T02:59:13.328Z", "removed_at": null, "description_excerpt": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning Carlsbad, California About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do You will lead an ML team building platforms and tooling to optimize supply allocation across our global satellite fleet to meet our customer demand, and provide business stakeholders with planning insights. This is a technical leadership role requiring strong engineering skills, product ownership, and the ability to contribute hands-on when needed. The day-to-day - Inform and execute the technical roadmap for satellite capacity optimization - Develop models, optimizations and tools for dynamic supply-demand optimization scenarios - Own the team backlog and translate stakeholder requirements into technical deliverables - Mentor ML engineers and data scientists, particularly on optimization problems - Get hands-on with complex technical challenges when your expertise is needed - Guide demand/supply modeling strategy and validate feasibility of optimization approaches - Partner with existing SMEs to drive development strategy - Interface with technical stakeholders to prioritize and scope work What you'll need - 10+ years in ML/optimization roles, with 3+ years leading technical teams - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.) - Proficient in SQL", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 44, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/797721/000119312526248290/vsat-20260331.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/797721/000119312526248290/vsat-20260331.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Retail", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": 10, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.39977adc38c98e1d67", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning Carlsbad, California About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do You will lead an ML team building platforms and tooling to optimize supply allocation across our global satellite fleet to meet our customer demand, and provide business stakeholders with planning insights. This is a technical leadership role requiring strong engineering skills, product ownership, and the ability to contribute hands-on when needed. The day-to-day - Inform and execute the technical roadmap for satellite capacity optimization - Develop models, optimizations and tools for dynamic supply-demand optimization scenarios - Own the team backlog and translate stakeholder requirements into technical deliverables - Mentor ML engineers and data scientists, particularly on optimization problems - Get hands-on with complex technical challenges when your expertise is needed - Guide demand/supply modeling strategy and validate feasibility of optimization approaches - Partner with existing SMEs to drive development strategy - Interface with technical stakeholders to prioritize and scope work What you'll need - 10+ years in ML/optimization roles, with 3+ years leading technical teams - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.) - Proficient in SQL", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:2d33b49d567d7e8bc84eff55718eca99:description:infinite", "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.ef1a4d2f32ce2c3277", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning Carlsbad, California About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do You will lead an ML team building platforms and tooling to optimize supply allocation across our global satellite fleet to meet our customer demand, and provide business stakeholders with planning insights. This is a technical leadership role requiring strong engineering skills, product ownership, and the ability to contribute hands-on when needed. The day-to-day - Inform and execute the technical roadmap for satellite capacity optimization - Develop models, optimizations and tools for dynamic supply-demand optimization scenarios - Own the team backlog and translate stakeholder requirements into technical deliverables - Mentor ML engineers and data scientists, particularly on optimization problems - Get hands-on with complex technical challenges when your expertise is needed - Guide demand/supply modeling strategy and validate feasibility of optimization approaches - Partner with existing SMEs to drive development strategy - Interface with technical stakeholders to prioritize and scope work What you'll need - 10+ years in ML/optimization roles, with 3+ years leading technical teams - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.) - Proficient in SQL", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:2d33b49d567d7e8bc84eff55718eca99:description:machine", "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.e6852fd11fa15822d4", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:2d33b49d567d7e8bc84eff55718eca99:title:machine", "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.semantic.description_excerpt.77c98065687b40d26a", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning Carlsbad, California About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do You will lead an ML team building platforms and tooling to optimize supply allocation across our global satellite fleet to meet our customer demand, and provide business stakeholders with planning insights. This is a technical leadership role requiring strong engineering skills, product ownership, and the ability to contribute hands-on when needed. The day-to-day - Inform and execute the technical roadmap for satellite capacity optimization - Develop models, optimizations and tools for dynamic supply-demand optimization scenarios - Own the team backlog and translate stakeholder requirements into technical deliverables - Mentor ML engineers and data scientists, particularly on optimization problems - Get hands-on with complex technical challenges when your expertise is needed - Guide demand/supply modeling strategy and validate feasibility of optimization approaches - Partner with existing SMEs to drive development strategy - Interface with technical stakeholders to prioritize and scope work What you'll need - 10+ years in ML/optimization roles, with 3+ years leading technical teams - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.) - Proficient in SQL", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:5d2314420f4924cccb5e3c23", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.efe3ff2ef436177bae", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning Carlsbad, California About us One team. Global challenges. Infinite opportunities. At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We're looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team. What you'll do You will lead an ML team building platforms and tooling to optimize supply allocation across our global satellite fleet to meet our customer demand, and provide business stakeholders with planning insights. This is a technical leadership role requiring strong engineering skills, product ownership, and the ability to contribute hands-on when needed. The day-to-day - Inform and execute the technical roadmap for satellite capacity optimization - Develop models, optimizations and tools for dynamic supply-demand optimization scenarios - Own the team backlog and translate stakeholder requirements into technical deliverables - Mentor ML engineers and data scientists, particularly on optimization problems - Get hands-on with complex technical challenges when your expertise is needed - Guide demand/supply modeling strategy and validate feasibility of optimization approaches - Partner with existing SMEs to drive development strategy - Interface with technical stakeholders to prioritize and scope work What you'll need - 10+ years in ML/optimization roles, with 3+ years leading technical teams - Strong background in optimization techniques (linear programming, constraint satisfaction, etc.) - Proficient in SQL", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.4c0a31c01276f85128", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "signal_type": "query_match", "display_text": "Title: \"machine\"", "tooltip": "Title contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Machine Learning Team Lead - Satellite Capacity Optimization & Planning", "matched_input": "machine", "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.0a575377503203597d", "query_id": "gq_d70e222980c74de92307", "job_id": "2d33b49d567d7e8bc84eff55718eca99", "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://careers-viasat.icims.com/jobs/5776/login", "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_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers-viasat.icims.com/jobs/5776/login", "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://careers-viasat.icims.com/jobs/5776/login", "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://careers-viasat.icims.com/jobs/5776/login", "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/797721/000119312526248290/vsat-20260331.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/797721/000119312526248290/vsat-20260331.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers-viasat.icims.com/jobs/5776/login", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers-viasat.icims.com/jobs/5776/login", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers-viasat.icims.com/jobs/5776/login", "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": "da9fe6126cf6a8292d833e71cccc8f25", "title": "Real-Time Systems Engineer", "employer_name": "Divergent 3D", "employer_slug": "divergent-3d", "location_text": "Torrance, 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": 141380, "salary_max": 224500, "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": 141380, "base_salary_max": 224500, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": true, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-06-09T18:25:29.000Z", "apply_url": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Real-Time Systems Engineer Torrance, California, United States Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that comprehensively uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures and subsystems. Products created using DAPS are superior in performance, lower in cost, rapidly customizable to meet mission and customer-specific requirements, faster to market, and scalable on demand to high volume production. Divergent is a qualified Tier 1 supplier to global automotive OEMs, and Divergent is now expanding to support mission critical needs in the Aerospace and Defense sector. Join us to be a part of this transformative journey, where your impact will shape the future of technology and production. Purpose We are seeking a talented and motivated Software Developer to join our Robotics & AI Software team. In this role, you will have the opportunity to work closely with experienced automation and software engineers to develop and implement innovative algorithms for task and motion planning plus computer vision in robotic systems. As a key member of our team, you will contribute to the design, development, and testing of software solutions aimed at enhancing the efficiency and reliability of robotic software algorithms. This involves symbolic task planning, robot kinematics, collision detection, optimization, and computer vision. The Role - Develop and maintain software development best practices to ensure high-quality code, efficient testing, and timely releases. - Collaborate with other teams to ensure that our", "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" }, "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" }, "health_plan_types": { "field": "health_plan_types", "source": "llm:greenfield:inv_371_postfix", "db_column": "health_plan_types" }, "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": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.description_excerpt.15f40e8b4b40bbc502", "query_id": "gq_d70e222980c74de92307", "job_id": "da9fe6126cf6a8292d833e71cccc8f25", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Real-Time Systems Engineer Torrance, California, United States Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that comprehensively uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures and subsystems. Products created using DAPS are superior in performance, lower in cost, rapidly customizable to meet mission and customer-specific requirements, faster to market, and scalable on demand to high volume production. Divergent is a qualified Tier 1 supplier to global automotive OEMs, and Divergent is now expanding to support mission critical needs in the Aerospace and Defense sector. Join us to be a part of this transformative journey, where your impact will shape the future of technology and production. Purpose We are seeking a talented and motivated Software Developer to join our Robotics & AI Software team. In this role, you will have the opportunity to work closely with experienced automation and software engineers to develop and implement innovative algorithms for task and motion planning plus computer vision in robotic systems. As a key member of our team, you will contribute to the design, development, and testing of software solutions aimed at enhancing the efficiency and reliability of robotic software algorithms. This involves symbolic task planning, robot kinematics, collision detection, optimization, and computer vision. The Role - Develop and maintain software development best practices to ensure high-quality code, efficient testing, and timely releases. - Collaborate with other teams to ensure that our", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:3a5e01afa6c0bb87d7b0d74d", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.0c665c79fc855eed79", "query_id": "gq_d70e222980c74de92307", "job_id": "da9fe6126cf6a8292d833e71cccc8f25", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Real-Time Systems Engineer Torrance, California, United States Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that comprehensively uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures and subsystems. Products created using DAPS are superior in performance, lower in cost, rapidly customizable to meet mission and customer-specific requirements, faster to market, and scalable on demand to high volume production. Divergent is a qualified Tier 1 supplier to global automotive OEMs, and Divergent is now expanding to support mission critical needs in the Aerospace and Defense sector. Join us to be a part of this transformative journey, where your impact will shape the future of technology and production. Purpose We are seeking a talented and motivated Software Developer to join our Robotics & AI Software team. In this role, you will have the opportunity to work closely with experienced automation and software engineers to develop and implement innovative algorithms for task and motion planning plus computer vision in robotic systems. As a key member of our team, you will contribute to the design, development, and testing of software solutions aimed at enhancing the efficiency and reliability of robotic software algorithms. This involves symbolic task planning, robot kinematics, collision detection, optimization, and computer vision. The Role - Develop and maintain software development best practices to ensure high-quality code, efficient testing, and timely releases. - Collaborate with other teams to ensure that our", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.3e680c8c246a16f6f3", "query_id": "gq_d70e222980c74de92307", "job_id": "da9fe6126cf6a8292d833e71cccc8f25", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:da9fe6126cf6a8292d833e71cccc8f25:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/divergent/jobs/5252722008", "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/divergent/jobs/5252722008", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "165f1c9d8093fb5bb5ba085a2f5f90aa", "title": "AI Coach", "employer_name": "Multiverse", "employer_slug": "multiverse", "location_text": "Remote (UK), UK, London", "country": "GB", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-05-18T15:00:31.725Z", "apply_url": "https://jobs.ashbyhq.com/multiverse/17a97d3e-6037-43e4-8224-306b1a81324b", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Coach Remote (UK), UK, London Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today's workforce. Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they've learned to improve productivity and measurable performance. In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK's first EdTech unicorn. But we aren't stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We're building a world where tech skills unlock people's potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era. The Opportunity As an AI Cohort Coach you will be responsible for guiding the learning experience for apprentices and helping them reach their full potential. Your role will be focusing on personalised coaching, where you'll be supporting apprentices across multiple businesses to become the next generation of business leaders. Specifically, You Will - Guide apprentices to successful, timely completion of their programme. - Master group and individualised coaching techniques to enhance apprentice learning. - Adhere to coach quality frameworks to ensure a consistent level of quality for every coaching session and", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "operations", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "masters", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.2bd6786fc74e908d29", "query_id": "gq_d70e222980c74de92307", "job_id": "165f1c9d8093fb5bb5ba085a2f5f90aa", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Coach", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:4c9ecd4b697b5eabe3393aeb", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.3526f2bbf5ffcbb2bb", "query_id": "gq_d70e222980c74de92307", "job_id": "165f1c9d8093fb5bb5ba085a2f5f90aa", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "operations", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:165f1c9d8093fb5bb5ba085a2f5f90aa:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/multiverse/17a97d3e-6037-43e4-8224-306b1a81324b", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/multiverse/17a97d3e-6037-43e4-8224-306b1a81324b", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/multiverse/17a97d3e-6037-43e4-8224-306b1a81324b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/multiverse/17a97d3e-6037-43e4-8224-306b1a81324b", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "00bf136ce41310638342747fa14e007f", "title": "Software Engineer 5 – Model Runtime, AI Platform", "employer_name": "Netflix", "employer_slug": "netflix", "location_text": "USA - Remote", "country": "US", "employment_type": "full_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": 466000, "salary_max": 750000, "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": 466000, "base_salary_max": 750000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": true, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-04-08T00:00:00.000Z", "apply_url": "https://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Software Engineer 5 – Model Runtime, AI Platform USA - Remote At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. Netflix is the world's leading streaming entertainment service, with over 300 million members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to optimizing our payment processing. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. The Opportunity The Model Runtime team owns the systems that train, align, and serve Netflix's most critical ML models. We are a small, highly autonomous team with outsized impact - the infrastructure we build directly shapes what Netflix can do with AI. We're looking for a Software Engineer who thrives at the intersection of systems engineering and ML. You will: Build alignment and post-training infrastructure - Design infrastructure for reinforcement learning (GRPO, DPO, PPO), reward modeling, and preference optimization so Netflix can train recommendation models directly against what members actually value. Enable next-generation GenAI workloads", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": 8, "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": 52, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1065280/000106528026000034/nflx-20251231.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" }, "bonus_offered": { "field": "bonus_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "bonus_offered" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1065280/000106528026000034/nflx-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" }, "mental_health_support": { "field": "mental_health_support", "source": "llm:greenfield:inv_371_postfix", "db_column": "mental_health_support" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" } }, "seniority": "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": "Media", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.description_excerpt.eb9fba18a7e5b5e8b5", "query_id": "gq_d70e222980c74de92307", "job_id": "00bf136ce41310638342747fa14e007f", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Software Engineer 5 – Model Runtime, AI Platform USA - Remote At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. Netflix is the world's leading streaming entertainment service, with over 300 million members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to optimizing our payment processing. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. The Opportunity The Model Runtime team owns the systems that train, align, and serve Netflix's most critical ML models. We are a small, highly autonomous team with outsized impact - the infrastructure we build directly shapes what Netflix can do with AI. We're looking for a Software Engineer who thrives at the intersection of systems engineering and ML. You will: Build alignment and post-training infrastructure - Design infrastructure for reinforcement learning (GRPO, DPO, PPO), reward modeling, and preference optimization so Netflix can train recommendation models directly against what members actually value. Enable next-generation GenAI workloads", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:4257279ca701dc3ff18ea96d", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ec91a4063f47fb18bd", "query_id": "gq_d70e222980c74de92307", "job_id": "00bf136ce41310638342747fa14e007f", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Software Engineer 5 – Model Runtime, AI Platform USA - Remote At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. Netflix is the world's leading streaming entertainment service, with over 300 million members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to optimizing our payment processing. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. The Opportunity The Model Runtime team owns the systems that train, align, and serve Netflix's most critical ML models. We are a small, highly autonomous team with outsized impact - the infrastructure we build directly shapes what Netflix can do with AI. We're looking for a Software Engineer who thrives at the intersection of systems engineering and ML. You will: Build alignment and post-training infrastructure - Design infrastructure for reinforcement learning (GRPO, DPO, PPO), reward modeling, and preference optimization so Netflix can train recommendation models directly against what members actually value. Enable next-generation GenAI workloads", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.54613982361ba3c01c", "query_id": "gq_d70e222980c74de92307", "job_id": "00bf136ce41310638342747fa14e007f", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:00bf136ce41310638342747fa14e007f:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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/1065280/000106528026000034/nflx-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1065280/000106528026000034/nflx-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "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://explore.jobs.netflix.net/careers/job/790315254643?microsite=netflix.com", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" } } }, { "id": "6a1100cb5284c5aa314bb6b12e29b5af", "title": "Sr. Technical Program Manager, AWS Rack Manufacturing", "employer_name": "Amazon", "employer_slug": "amazon", "location_text": "SGP", "country": "SG", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "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": true, "childcare_subsidy": true, "fertility_family_building_benefits": true, "adoption_assistance_offered": true, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-04T00:00:00.000Z", "apply_url": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "apply_url_verified": false, "ats": "amazon_custom", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "parental_leave_weeks": 6, "non_birth_parent_leave_weeks": 6, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 52, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families", "db_column": "parental_leave_weeks", "source_url": "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" }, "mental_health_support": { "field": "mental_health_support", "source": "llm:greenfield:inv_371_postfix", "db_column": "mental_health_support" }, "adoption_assistance_offered": { "field": "adoption_assistance_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "adoption_assistance_offered" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" }, "fertility_family_building_benefits": { "field": "fertility_family_building_benefits", "source": "llm:greenfield:inv_371_postfix", "db_column": "fertility_family_building_benefits" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Industrial", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "bachelors", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3a14ba7acd78642004", "query_id": "gq_d70e222980c74de92307", "job_id": "6a1100cb5284c5aa314bb6b12e29b5af", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description matched \"infinite\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "matched_input": "infinite", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6a1100cb5284c5aa314bb6b12e29b5af:description:infinite", "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.95ca97f67c06423a4c", "query_id": "gq_d70e222980c74de92307", "job_id": "6a1100cb5284c5aa314bb6b12e29b5af", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description matched \"machine\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "matched_input": "machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:6a1100cb5284c5aa314bb6b12e29b5af:description:machine", "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.semantic.description_excerpt.0443add608f0686f9c", "query_id": "gq_d70e222980c74de92307", "job_id": "6a1100cb5284c5aa314bb6b12e29b5af", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:cb4e170bf9590cab4e19d4ef", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.4d83c9455efaa80c7a", "query_id": "gq_d70e222980c74de92307", "job_id": "6a1100cb5284c5aa314bb6b12e29b5af", "signal_type": "query_match", "display_text": "Description: \"machine\"", "tooltip": "Description contains \"machine\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "matched_input": "machine", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.6eed4aad93746f98ac", "query_id": "gq_d70e222980c74de92307", "job_id": "6a1100cb5284c5aa314bb6b12e29b5af", "signal_type": "query_match", "display_text": "Description: \"infinite\"", "tooltip": "Description contains \"infinite\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Technical Program Manager, AWS Rack Manufacturing SGP AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. We are seeking a Manufacturing Operations and Industrial Engineering Program Manager to help us fuel AWS' explosive growth. This role is the single-threaded owner of factory layout and material flow design across AWS rack fulfillment manufacturing sites. You will work at the intersection of capacity planning, automation engineering, construction, and operations - spanning EC2, Machine Learning, and Storage hardware platforms in AWS manufacturing. Your work directly enables AWS to meet datacenter capacity commitments by ensuring manufacturing infrastructure scales efficiently, reliably, and repeatably across a global site network. Possessing strong leadership,", "matched_input": "infinite", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1018724/000101872426000004/amzn-20251231.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "https://www.aboutamazon.com/news/workplace/what-20-weeks-of-fully-paid-leave-does-for-Amazon-families" ], "checked_at": "2026-06-07T00:00:00Z" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "fertility_family_building_benefits": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "mental_health_support": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "adoption_assistance_offered": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://www.amazon.jobs/en/jobs/10440128/sr-technical-program-manager-aws-rack-manufacturing", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-07T00:00:00Z" } } }, { "id": "d0e0f5e0bf364be1aaf9e4fe751a37e0", "title": "GTM Enablement - Expansion", "employer_name": "ElevenLabs", "employer_slug": "elevenlabs", "location_text": "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", "a16z", "sequoia" ], "posted_at": "2026-04-03T17:46:50.904Z", "apply_url": "https://jobs.ashbyhq.com/elevenlabs/eee2abfb-bd2f-410d-a339-3923e9c95043", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "GTM Enablement - Expansion United States About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don't have job titles. Instead, it's about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 4, "years_experience_max": 11, "role_function": "operations", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.c6b88a9f9a859c6624", "query_id": "gq_d70e222980c74de92307", "job_id": "d0e0f5e0bf364be1aaf9e4fe751a37e0", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "GTM Enablement - Expansion", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:6a04b2c679018df6c84ea2e9", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.4a1147948e56935071", "query_id": "gq_d70e222980c74de92307", "job_id": "d0e0f5e0bf364be1aaf9e4fe751a37e0", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "operations", "matched_input": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d0e0f5e0bf364be1aaf9e4fe751a37e0:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/elevenlabs/eee2abfb-bd2f-410d-a339-3923e9c95043", "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/elevenlabs/eee2abfb-bd2f-410d-a339-3923e9c95043", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "72877895b994e4adbd9bdba34d0a0a01", "title": "Principal Engineer, Autonomous Vehicles and Physical AI Solutions", "employer_name": "NVIDIA Corporation", "employer_slug": "nvidia", "location_text": "Japan, Tokyo", "country": "JP", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Japan-Tokyo/Principal-Engineer--Autonomous-Vehicles-and-Physical-AI-Solutions_JR2015317", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Principal Engineer, Autonomous Vehicles and Physical AI Solutions Japan, Tokyo posted: Posted 30+ Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "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.title.7a2f0d4402e1a01f1a", "query_id": "gq_d70e222980c74de92307", "job_id": "72877895b994e4adbd9bdba34d0a0a01", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Principal Engineer, Autonomous Vehicles and Physical AI Solutions", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:b218975115b17ba02a124ecd", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c0fbdc02a991534fd0", "query_id": "gq_d70e222980c74de92307", "job_id": "72877895b994e4adbd9bdba34d0a0a01", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:72877895b994e4adbd9bdba34d0a0a01:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-13T01:18:42.546Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Japan-Tokyo/Principal-Engineer--Autonomous-Vehicles-and-Physical-AI-Solutions_JR2015317", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/Japan-Tokyo/Principal-Engineer--Autonomous-Vehicles-and-Physical-AI-Solutions_JR2015317", "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": "5b437789b3adb5a396be21d194d77c7b", "title": "Systems Software Developer - Nonstop OS", "employer_name": "Hewlett Packard Enterprise", "employer_slug": "hewlett-packard-enterprise", "location_text": "Bengaluru, Karnātaka, 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" ], "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": true, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-27T00:00:00.000Z", "apply_url": "https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Bengaluru-Karntaka-India/Systems-Software-Developer---Nonstop-OS_1206841-1/apply", "apply_url_verified": false, "ats": "phenom_people", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Systems Software Developer - Nonstop OS Bengaluru, Karnātaka, India Join our team as a Senior Systems Software Developer and drive innovation in high-performance computing. Leverage your expertise in C/C++, TAL, and system internals to design, develop, and support mission-critical software. Collaborate with top engineers and help shape the future of digital transformation at Hewlett Packard Enterprise.", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-13T01:18:42.546Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1645590/000164559025000130/hpe-20251031.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" }, "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/1645590/000164559025000130/hpe-20251031.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "childcare_subsidy": { "field": "childcare_subsidy", "source": "llm:greenfield:inv_371_postfix", "db_column": "childcare_subsidy" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": 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": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.333062310707615dd6", "query_id": "gq_d70e222980c74de92307", "job_id": "5b437789b3adb5a396be21d194d77c7b", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Systems Software Developer - Nonstop OS", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:8df8d07f640a351f49a13557", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.54fcde0ec86d5d6639", "query_id": "gq_d70e222980c74de92307", "job_id": "5b437789b3adb5a396be21d194d77c7b", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:5b437789b3adb5a396be21d194d77c7b: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/1645590/000164559025000130/hpe-20251031.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1645590/000164559025000130/hpe-20251031.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://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Bengaluru-Karntaka-India/Systems-Software-Developer---Nonstop-OS_1206841-1/apply", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Bengaluru-Karntaka-India/Systems-Software-Developer---Nonstop-OS_1206841-1/apply", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "childcare_subsidy": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Bengaluru-Karntaka-India/Systems-Software-Developer---Nonstop-OS_1206841-1/apply", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-13T01:18:42.546Z" } } }, { "id": "d4846a14e32159ae3c6016ea732f7840", "title": "Applied AI Engineer", "employer_name": "Fuse Energy", "employer_slug": "fuse-energy", "location_text": "Location not specified", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2025-02-11T00:00:00.000Z", "apply_url": "https://apply.workable.com/j/64F3A20A10", "apply_url_verified": false, "ats": "workable", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI Engineer", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Energy", "employer_industry_source": "source_sector", "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.title.9aad6e47e405a701c0", "query_id": "gq_d70e222980c74de92307", "job_id": "d4846a14e32159ae3c6016ea732f7840", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Applied AI Engineer", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:1f50247fc94791ca4341e1df", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.01e6a05dd45a9a1af3", "query_id": "gq_d70e222980c74de92307", "job_id": "d4846a14e32159ae3c6016ea732f7840", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:d4846a14e32159ae3c6016ea732f7840: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://apply.workable.com/j/64F3A20A10", "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://apply.workable.com/j/64F3A20A10", "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": "786aa50c89f7a63cae083fab85fa0875", "title": "Engineering Manager, Fleet Reliability", "employer_name": "Fal", "employer_slug": "fal", "location_text": "Remote", "country": "unknown", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": 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": "2026-05-14T04:40:27.000Z", "apply_url": "https://job-boards.greenhouse.io/fal/jobs/4248334009", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Engineering Manager, Fleet Reliability Remote 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. About the role We're hiring an Engineering Manager to build and run Fleet Reliability: the function that keeps every GPU node we own provisioned, validated, and alive. The fleet is about to 10x. You'll hire the team, set the bar, write the playbooks, and own the operating model. You're a fit if you've: - 7+ years in infrastructure, software, or SRE, with 2+ years leading - Run a fleet reliability or hardware ops team in production - Built SRE fundamentals into a team from scratch: incident management, postmortems, observability, change management - Pushed teams toward automation over toil Who you are: - Player-coach. - Process-oriented without being bureaucratic - Allergic to toil. Every recurring problem is an automation opportunity - Carry the pager yourself before asking your team to Responsibilities: - Build and lead the Fleet Reliability team: hire, develop, retain - Own 24/7", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "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" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": true, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.4f6e0c76cb1c207f96", "query_id": "gq_d70e222980c74de92307", "job_id": "786aa50c89f7a63cae083fab85fa0875", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Engineering Manager, Fleet Reliability", "matched_input": "infinite machine", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:e524e5c1c467865b6a6ce629", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.b0d0aaeb698d4b5549", "query_id": "gq_d70e222980c74de92307", "job_id": "786aa50c89f7a63cae083fab85fa0875", "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": "infinite machine", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_d70e222980c74de92307:786aa50c89f7a63cae083fab85fa0875:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/fal/jobs/4248334009", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/fal/jobs/4248334009", "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/4248334009", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } } ], "total": 45, "page": 1, "per_page": 24, "applied_filters": { "q": "Infinite Machine" }, "hidden_unknown_benefits_count": 0, "hidden_quality_floor_count": 0, "quality_floor": "default", "search_profile": { "profile_id": "inv382.d6.pg_textsearch_bge_small_rrf.v1", "bm25_extension": "pg_textsearch", "vector_model": "BAAI/bge-small-en-v1.5", "vector_model_version": "v1.5", "fusion_method": "rrf" }, "explanation_context": { "non_trivial_query": true, "query_terms": [ "infinite", "machine" ], "active_filter_keys": [], "visible_signal_limit": 3, "visible_trust_limit": 2 }, "event_context": { "query_context": { "query_id": "f9964473-62e4-4140-9bbd-2b5e52e37c0f", "issued_at": "2026-08-18T13:28:25.311Z", "route": "/jobs", "page": 1, "per_page": 24, "total_results": 45, "sort": "relevance", "ranking_policy": "hybrid_rrf_rerank", "ranking_policy_version": "inv382.jobs.search.v2", "query_hash": "hmac_sha256:_eEHd_ayd_2qrBcLZBpmyvJ2991BI6eXmC8_yMuvUZA", "filter_hash": "hmac_sha256:6CBErDPXOFVCSNkSGbTmuw6GxoMjwSLro0KqZMtxL_0", "query_features": { "has_q": true, "q_term_count": 2, "q_length_bucket": "16_40", "q_pii_redacted": false, "state_count": 0, "benefit_filters": [], "quality_floor": "default" }, "exposures": [ { "result_id": "8a9f8fd5284fc0d9b34ef3c663bf8435", "position": 1, "page_position": 1, "retrieval_features": { "bm25_score": -15.035911560058594, "vector_score": 0.3303002515524698, "rrf_score": 0.032266458495966696, "rerank_score": 7.152464866638184, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 126, "quality_score": 45 } }, { "result_id": "f9647dd27f6fb442aca9db875d6e686c", "position": 2, "page_position": 2, "retrieval_features": { "bm25_score": -14.105779647827148, "vector_score": 0.29764389991760254, "rrf_score": 0.03252247488101534, "rerank_score": 6.579649448394775, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 687, "quality_score": 45 } }, { "result_id": "d92be948229a9d4191d4219d2d35bec3", "position": 3, "page_position": 3, "retrieval_features": { "bm25_score": -10.38448429107666, "vector_score": 0.31989866495132446, "rrf_score": 0.03200204813108039, "rerank_score": 6.277886867523193, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 88, "quality_score": 45 } }, { "result_id": "642d49047e2218f11db6b8281e46cc1c", "position": 4, "page_position": 4, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3492581844329834, "rrf_score": 0.015625, "rerank_score": -2.1731326580047607, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 69, "quality_score": 45 } }, { "result_id": "6f7bfb60299046c0d68321ef39b68dc1", "position": 5, "page_position": 5, "retrieval_features": { "bm25_score": -9.002863883972168, "vector_score": 0.3812268745167915, "rrf_score": 0.02804284323271665, "rerank_score": -6.020097255706787, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 69, "quality_score": 55 } }, { "result_id": "8d302b50361fea98136c627ca9a978e0", "position": 6, "page_position": 6, "retrieval_features": { "bm25_score": -7.816661834716797, "vector_score": 0.37242684528667547, "rrf_score": 0.029236022193768675, "rerank_score": -6.161896228790283, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 67, "quality_score": 45 } }, { "result_id": "8bb9a6209b485049dae509abceb27989", "position": 7, "page_position": 7, "retrieval_features": { "bm25_score": -7.379188060760498, "vector_score": 0, "rrf_score": 0.013888888888888888, "rerank_score": -7.672069549560547, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 69, "quality_score": 45 } }, { "result_id": "6330ade0d4f894a03896bfa712703661", "position": 8, "page_position": 8, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3805976283194037, "rrf_score": 0.013157894736842105, "rerank_score": -10.209568977355957, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 98, "quality_score": 35 } }, { "result_id": "575378268580284e7662d189550be993", "position": 9, "page_position": 9, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3755803108215332, "rrf_score": 0.014925373134328358, "rerank_score": -10.374550819396973, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 67, "quality_score": 35 } }, { "result_id": "09a13e8db232dfa8d4e0a147fb63bd92", "position": 10, "page_position": 10, "retrieval_features": { "bm25_score": -7.176406383514404, "vector_score": 0, "rrf_score": 0.012987012987012988, "rerank_score": -10.505088806152344, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 76, "quality_score": 35 } }, { "result_id": "771f64bb391f17ea2944f692ff793fcd", "position": 11, "page_position": 11, "retrieval_features": { "bm25_score": 0, "vector_score": 0.37851897606140406, "rrf_score": 0.013513513513513514, "rerank_score": -10.58620834350586, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 173, "quality_score": 45 } }, { "result_id": "41c90c40d04442fc7d6740254dc0da6f", "position": 12, "page_position": 12, "retrieval_features": { "bm25_score": -8.751921653747559, "vector_score": 0, "rrf_score": 0.015151515151515152, "rerank_score": -10.606979370117188, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 199, "quality_score": 45 } }, { "result_id": "b31b972ed07e4e83e4fa38a0ac60b6fb", "position": 13, "page_position": 13, "retrieval_features": { "bm25_score": -7.223166465759277, "vector_score": 0, "rrf_score": 0.013157894736842105, "rerank_score": -10.722949981689453, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 88, "quality_score": 35 } }, { "result_id": "d7422cc37539c48db779d56be8a5d8c4", "position": 14, "page_position": 14, "retrieval_features": { "bm25_score": -8.292608737945557, "vector_score": 0, "rrf_score": 0.014492753623188406, "rerank_score": -10.730690956115723, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 480, "quality_score": 45 } }, { "result_id": "2d33b49d567d7e8bc84eff55718eca99", "position": 15, "page_position": 15, "retrieval_features": { "bm25_score": -8.292608737945557, "vector_score": 0, "rrf_score": 0.014705882352941176, "rerank_score": -10.816108703613281, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 119, "quality_score": 55 } }, { "result_id": "da9fe6126cf6a8292d833e71cccc8f25", "position": 16, "page_position": 16, "retrieval_features": { "bm25_score": 0, "vector_score": 0.376295126897386, "rrf_score": 0.014285714285714285, "rerank_score": -11.306618690490723, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 69, "quality_score": 55 } }, { "result_id": "165f1c9d8093fb5bb5ba085a2f5f90aa", "position": 17, "page_position": 17, "retrieval_features": { "bm25_score": 0, "vector_score": 0.38075679540634155, "rrf_score": 0.012987012987012988, "rerank_score": -11.309671401977539, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 91, "quality_score": 45 } }, { "result_id": "00bf136ce41310638342747fa14e007f", "position": 18, "page_position": 18, "retrieval_features": { "bm25_score": 0, "vector_score": 0.37675124406814575, "rrf_score": 0.013888888888888888, "rerank_score": -11.42647933959961, "text_match_title": false, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 132, "quality_score": 55 } }, { "result_id": "6a1100cb5284c5aa314bb6b12e29b5af", "position": 19, "page_position": 19, "retrieval_features": { "bm25_score": -7.316614627838135, "vector_score": 0, "rrf_score": 0.013333333333333334, "rerank_score": -11.4332857131958, "text_match_title": false, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 75, "quality_score": 45 } }, { "result_id": "d0e0f5e0bf364be1aaf9e4fe751a37e0", "position": 20, "page_position": 20, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3763524889945984, "rrf_score": 0.014084507042253521, "rerank_score": -11.44771671295166, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 136, "quality_score": 45 } }, { "result_id": "72877895b994e4adbd9bdba34d0a0a01", "position": 21, "page_position": 21, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3794175386428833, "rrf_score": 0.013333333333333334, "rerank_score": -11.4619140625, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 98, "quality_score": 35 } }, { "result_id": "5b437789b3adb5a396be21d194d77c7b", "position": 22, "page_position": 22, "retrieval_features": { "bm25_score": 0, "vector_score": 0.3757256269454956, "rrf_score": 0.014492753623188406, "rerank_score": -11.462828636169434, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 83, "quality_score": 45 } }, { "result_id": "d4846a14e32159ae3c6016ea732f7840", "position": 23, "page_position": 23, "retrieval_features": { "bm25_score": 0, "vector_score": 0.37842740883990467, "rrf_score": 0.0136986301369863, "rerank_score": -11.470918655395508, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 553, "quality_score": 35 } }, { "result_id": "786aa50c89f7a63cae083fab85fa0875", "position": 24, "page_position": 24, "retrieval_features": { "bm25_score": 0, "vector_score": 0.37564516067504883, "rrf_score": 0.014705882352941176, "rerank_score": -11.472338676452637, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 96, "quality_score": 45 } } ] }, "context_signature": "ueQH7Zc1604jGAM-uMHuojfn1e3jQstoHy1ThXJSPPQ", "event_token": "ueQH7Zc1604jGAM-uMHuojfn1e3jQstoHy1ThXJSPPQ" } }