{"id":2228624,"url":"https://alion.io/job/general-motors-staff-ml-systems-engineer","title":"Staff ML Systems Engineer","company":{"id":1705,"name":"General Motors","domain":"gm.com","url":"https://alion.io/company/general-motors-europe","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":63,"ghost_share":0,"stale_share":0.841,"repost_share":0,"time_to_fill_p50_days":12,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States","Washington, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":171700,"max":303900,"currency":"USD","period":"year","gross":null,"usd_annual":303900},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"CI/CD","optional":false},{"name":"Go","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Redux","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"A/B Testing","optional":true},{"name":"Computer Vision","optional":true},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-22T05:31:12Z","board_verified":false,"closed_at":null,"days_open":25,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":24},"description":"Job Description\nHelp teach our self-driving vehicles how to see and understand the world!\nThe Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models within General Motors' AV organization. We operate in the intersection of software engineering, data engineering, and AI/ML, defining the strategies, tooling, and quality controls that create reliable training data at scale. Our tools and platform are used by thousands of users and consumers.\nWe own a modern full-stack architecture including TypeScript/React, Python, GraphQL, Golang, and ML model services, which powers data-annotation pipelines and machine-led training data solutions at foundation-model scale. We partner closely across AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups.\nThis role is ideal for an engineer looking for end-to-end ownership of meaningful pieces of the platform, growth in technical and strategic leadership, and direct impact across teams and systems that unblock the next generation of AV capabilities.\nWhat You’ll Do\nDefine the platform vision and roadmap Work with cross-team and cross-functional leads to understand current and future needs, translating their input into an aligned platform vision and an incremental development roadmap.\nOwn projects end-to-end Take ownership of technical projects from problem framing through design, implementation, and rollout. Drive code reviews, design discussions, and technical decisions.\n Collaborate across the AV stack Work with partner teams (ML Engineering, Operations, Product, Data Science, other platform teams) to translate abstract requirements into concrete workflows, APIs, and UIs that hit quality, cost, and latency goals.\n Level up how ML teams work with data Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, auto-QA, autolabel review tools), reducing iteration time from idea to trained model.\n Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops), helping us move from human-only to machine-led labeling at scale.\nBuild high-impact labeling experiences Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies. You’ll help the team ship features spanning multiple surface-areas that directly affect how quickly and accurately we can label data for new models and cities.\n Champion AI-assisted engineering Use and advocate for modern AI-powered development workflows (code assistants, automated documentation, test generation, etc.) to increase build-velocity while maintaining code and product quality.\nYour Skills & Abilities\nPassionate about self-driving/robotics technology and its potential to transform safety, mobility, and the human experience.\nProven experience shipping and operating end-to-end products or features in production.\nStrong communication and collaboration skills; you can explain tradeoffs, influence peers, and work through ambiguity with cross-functional partners.\nDriven to learn new technologies and deepen your expertise across frontend, backend, and data/ML-adjacent systems.\nEmpathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools.\nRequirements\n8+ years of experience building robust distributed platforms and applications.\nHands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.\nProficiency in writing and reviewing high-quality, scalable, and performant full-stack code using technologies and languages like Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, etc.\nSolid understanding of scalable software system design including data modeling and API/interface design.\nStrong fundamentals in object-oriented design and design patterns, data structures, algorithms, and engineering best practices (TDD, code quality, observability, CI/CD).\nBonus Points\nA track record of close collaboration with customers, product managers, designers, and/or user experience researchers.\nExperience with computer vision, machine learning, or data-centric AI projects - especially where data annotation, data quality, or autolabeling loops were central to the work.\nFamiliarity with data labeling/annotation platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems).\nExperience with A/B testing and telemetry/observability systems to measure impact and reliability.\nExperience developing data-intensive or visualization-heavy applications.\nCompensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.\nThe salary range for this role: is $171,700 to $303,900. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. \nBonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. \nBenefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.\n\nThis role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.\n\nThe selected candidate will be required to travel About GMOur vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.\nWhy Join Us\nWe believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.\nBenefits Overview\nFrom day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.\nNon-Discrimination and Equal Employment Opportunities (U.S.)\nGeneral Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.\nAll employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.\nWe encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.\nAccommodations\nGeneral Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.","description_format":"text","description_chars":8441,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Life insurance","Retirement plans"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Automotive Manufacturing"],"lifecycle":[{"event":"open","at":"2026-10-10T17:37:23Z"},{"event":"close","at":"2026-10-19T10:50:38Z"},{"event":"reopen","at":"2026-10-20T13:42:53Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 795 · green card filings: 1","filings_12m":795,"filings_prev_12m":812,"green_card_filings_12m":1,"median_offered_wage_usd":147456,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":348}],"liveness":{"score":13,"band":"cold","label":"Long shot","p_open":0.9,"p_active":0.417,"p_room":0.35,"age_days":24,"expected_fill_days":12,"reasons":["conf:48","stale_co","velocity","win:tail","comp:brand"],"computed_at":"2026-10-24T06:02:35Z"},"pay":{"stated_usd_annual":303900,"is_top_pay":true},"html_url":"https://alion.io/job/general-motors-staff-ml-systems-engineer","json_url":"https://alion.io/job/general-motors-staff-ml-systems-engineer.json","meta":{"generated_at":"2026-10-25T00:00:52Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":20,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1705},"rest":"https://alion.io/mcp/rest/get_company?id=1705"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgeneral-motors-staff-ml-systems-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fgeneral-motors-staff-ml-systems-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fgeneral-motors-staff-ml-systems-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/general-motors-staff-ml-systems-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgeneral-motors-staff-ml-systems-engineer"}]}