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ML Systems Engineer

  • 위치
    • Mountain View, California
    • Remote
    • Sunnyvale, California
  • 직무 유형 Full time
  • 게시됨
  • Job Requisition JR-202602436

설명

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

The Data Labeling Engineering team designs, builds, and operates high‑quality hybrid human/machine labeling tools and pipelines that power autonomous vehicle machine learning models across General Motors . We sit at the intersection of software engineering , data engineering , and ML , defining labeling strategies, tooling, and quality controls that create reliable training data at scale.

Our team builds the mission‑critical products that let people and machines add “ground truth” labels to roads, objects, and complex driving scenarios in sensor data from self‑driving cars. These tools are used by thousands of labelers and dozens of ML teams to train and evaluate the models behind advanced driver assistance and autonomous features.

We own a modern full‑stack architecture including TypeScript, React, GraphQL, Python, Golang , and ML model services , leveraging cloud platforms and workflow orchestration tools (e.g., Airflow ) to power data‑annotation pipelines and ML‑led labeling solutions at foundation‑model scale . We partner closely with ML engineers , Operations , Product Management , Data Science , and other ML Platform groups.

This role is ideal for an engineer who wants to own meaningful pieces of the stack, grow toward technical leadership, and work directly on systems that unblock the next generation of AV models.

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 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‑in‑the‑loop labeling at scale.

  • 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.

  • 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.

Your Skills & Abilities (Required Qualifications)

General

  • 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 .

Technical

  • 2+ years of experience building robust web applications .

  • Bachelors degree or higher in Computer Science or related field. Or relevant work experience.

  • Hands‑on experience leveraging AI tools (agentic coding, search, documentation generators) to accelerate understanding, implementation, and delivery of customer value.

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

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

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

  • Experience developing and operating cloud‑based applications .

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

What Will Give You a Competitive Edge (preferred qualifications):

  • 4+ years of experience in the software .

  • 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).

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  $90,100 to $191,800 . 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: 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.

이 직무는 하이브리드 직무로 분류됩니다. 즉, 선발된 지원자는 특정 근무지로 주 3일 이상(또는 관리자가 지정한 다른 빈도로) 특정 근무지로 출근해야 합니다.

선발된 지원자는 이 직무를 위해 25% 미만의 출장을 다녀야 합니다.

이 직무는 리로케이션 혜택을 받을 수 있습니다.

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.