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Staff ML Systems Engineer

Sunnyvale, California, United States of America

Live, first seen by us 85 days ago
Pay
$171,700–303,900/yearAnnual period assumed — pay source
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 $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. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Own technical projects end-to-end, from problem framing through rollout

  • Define the platform vision and incremental development roadmap

  • Integrate ML-driven pre-labeling and autolabeling into annotation workflows

  • Build automation and dashboards giving ML engineers insight into labeling quality

  • Design and build scalable full-stack labeling user experiences and services

From the employer’s posting
Take ownership of technical projects from problem framing through design, implementation, and rollout.
Define the platform vision and roadmap
Collaborate with ML engineers to design and integrate ML‑driven data annotation (pre‑labeling, autolabeling, active learning loops)
Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality
Design, implement, and test scalable, high‑performance user experiences and services using modern full‑stack and/or frontend technologies.

What you’ll bring

All qualifications

Core experience

  • 8+ years of experience building robust distributed platforms and applications.
  • Experience with computer vision, machine learning, or data‑centric AI projects — especially where data annotation, data quality, or autolabeling loops were central to the work.
  • Hands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.
  • Familiarity with data labeling/annotation platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems).
  • Proficiency 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.
  • Experience with A/B testing and telemetry/observability systems to measure impact and reliability.
Qualification wording
8+ years of experience building robust distributed platforms and applications.
Experience with computer vision, machine learning, or data‑centric AI projects — especially where data annotation, data quality, or autolabeling loops were central to the work.
Hands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.
Familiarity with data labeling/annotation platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems).
Proficiency 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.
Experience with A/B testing and telemetry/observability systems to measure impact and reliability.
Apply at General Motors

Posting record

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Status in our records
Live
First seen by us
Aug 13, 202685 days ago
Recorded sightings
189
Last seen by us
Nov 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$172K–$304K against $166K–$240K, the middle half of what similar US postings state.

From 1,319 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 85

Up longer than most. Similar jobs usually come down between day 6 and day 71.

Well past General Motors’s usual: its jobs come down by about day 14.

From 4,633 similar postings that came down, and 135 of General Motors’s. Coming down is not always a hire.

General Motors is hiring

48 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring is picking up
  • Takes jobs down at a usual pace
  • 6% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Go
  • Python
  • SQL
  • TypeScript
  • React
Where the posting names them
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 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.
- Hands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, 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, gRPC, GraphQL, WebGL, etc. - Solid understanding of scalable software system design including data modeling and API/interface design.

Your next step

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About General Motors

People
About 13,474 in 2025.Benefit plan filings (Form 5500)
Company
Listed as GM.
H-1B visas
163 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 624, the most 1,094, and the latest week had 870.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Job Description

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 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.

What You’ll Do

  • Define 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.
  • 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 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.
  • 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.
  • 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 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.
  • 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.

Your Skills & Abilities

  • Passionate about self‑driving/robotics technology and its potential to transform safety, mobility, and the human experience.
  • 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.
  • Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML‑adjacent systems.
  • Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools.

Requirements

  • 8+ years of experience building robust distributed platforms and applications.
  • Hands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, 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, gRPC, GraphQL, WebGL, etc.
  • Solid understanding of scalable software system design including data modeling and API/interface design.
  • Strong fundamentals in object‑oriented design and design patterns, data structures, algorithms, and engineering best practices (TDD, code quality, observability, CI/CD).

Bonus Points

  • A track record of close collaboration with customers, product managers, designers, and/or user experience researchers.
  • Experience with computer vision, machine learning, or data‑centric AI projects — especially where data annotation, data quality, or autolabeling loops were central to the work.
  • Familiarity with data labeling/annotation 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.
  • Experience developing data‑intensive or visualization‑heavy applications.

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 $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. 
  • 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.
&#xa;&#xa;&#xa;&#xa;This 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}.&#xa;&#xa;The selected candidate will be required to travel <25% for this role.&#xa;&#xa;Relocation benefits are available for candidates who qualify under company policy.&#xa;&#xa;

About GM

Our 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.

Why Join Us 

We 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.

Benefits Overview

From 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.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General 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.

All 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. 

We 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.

Accommodations

General 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.

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Pay
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 $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. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Location & working pattern

Sunnyvale, California, United States of America

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.
More source context
- 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. &#xa;&#xa;&#xa;&#xa;This 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}.&#xa;&#xa;The selected candidate will be required to travel <25% for this role.&#xa;&#xa;Relocation benefits are available for candidates who qualify under company policy.&#xa;&#xa;About GM Our 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.
Work authorization
General 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. All 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. We 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.

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