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Senior AI/ML Engineer

  • 위치
    • Remote
    • Sunnyvale, California
  • 직무 유형 Full time
  • 게시됨
  • Job Requisition JR-202609267

설명

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA you are expected to report to that location three times a week.

Help teach our self‑driving vehicles how to see and understand the world!


The 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.


We 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.


This role is ideal for an engineer who wants end-to-end ownership of meaningful pieces of the platform, growth toward technical leadership, and direct impact on systems that unblock the next generation of AV capabilities.

What You’ll Do

  • Build 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 ship features spanning multiple surface-areas that directly affect how quickly and accurately we can label data for new models and cities.

  • 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.

  • 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.

  • Champion AI‑assisted engineering
    Use and advocate for modern AI‑powered development workflows (code assistants, automated documentation, test generation, etc.) to increase velocity while maintaining quality.

  • Own 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.

  • Collaborate across the AV stack
    Work with partner teams (ML, Ops, Product, Data Science, other platform teams) to translate abstract requirements into concrete workflows, APIs, and UIs that hit quality, cost, and latency goals.

Your Skills & Abilities

  • Passionate about self‑driving technology and its potential to transform safety, mobility, and the driving experience.

  • Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML‑adjacent systems.

  • Proven experience shipping and operating end‑to‑end products or features in production.

  • Strong communication and collaboration skills; you can explain tradeoffs, influence peers, and work through ambiguity with cross‑functional partners.

  • Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools.

Requirements

  • 6+ years of experience building robust distributed platforms and applications.

  • Hands-on experience leveraging AI tools (agentic coding, search, documentation generators, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.

  • Proficiency in writing and reviewing high‑quality, scalable, and performant full-stack code using technologies and languages like Python, TypeScript, Go, React, SQL, Redux, GraphQL, WebGL.

  • Solid understanding of relational databases, data modeling, and API design.

  • Strong fundamentals in object‑oriented design and design patterns, data structures, algorithms, and engineering best practices (TDD, code quality, observability, CI/CD).

  • Experience developing and operating cloud‑based applications.

Bonus Points

  • Experience using modern web APIs (Service Workers, Cache Storage, IndexedDB, etc.) in data‑intensive or visualization‑heavy applications.

  • A track record of close collaboration with customers, product managers, designers, and user experience researchers.

  • Experience with computer vision, machine learning, or data‑centric AI projects — especially where labeled data, data quality, or autolabeling loops were central to the work.

  • Familiarity with data labeling platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems).

  • Experience with A/B testing and telemetry/observability systems to measure impact and reliability.

  • Proficiency in writing and reviewing high‑quality, scalable, and performant code using TypeScript, React, Redux, GraphQL, WebGL, or similar frontend technologies.

Compensation : 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.  

  • The salary range for this role is  $170,600 to $261,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. 

  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. 

Benefits:  

  • Benefits: 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. 

다양성 정보

General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다.  자세한 정보는 GM 채용 과정 안내를 참고하십시오.

공평한 취업 기회 선언 (미국)

General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다.  자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다. 

숙소 (미국 및 캐나다)

General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.