Pay
In line with similar jobs
$145K–$261K 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.
Senior AI/ML Performance Engineer
Sunnyvale, California, United States of America
Open 6 months, first seen by us 198 days ago- Pay
$144,700–261,300/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 $144,700 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.
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 postingAnalyze production workloads in depth to find bottlenecks
Propose and run high-impact performance optimization projects
Design architecture changes to scale large ML training and inference environments
Work with AI/ML research, infrastructure, and cloud vendor teams on projects
From the employer’s posting
Conduct deep-dive analyses of production workloads to identify bottlenecks
propose high-impact optimization strategies
Identify opportunities for architectural improvements to ensure the scalability and reliability of large-scale ML training and inference environments
Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors
Education & alternatives
- Experience: 5+ years of professional experience in high-scale infrastructure or ML systems. - Education: Bachelor’s Degree in Computer Science, a related technical field, or equivalent practical experience. - Software Proficiency: Expert-level coding skills in Python and the ability to architect/debug within the PyTorch ecosystem.
About General Motors
The AV Infrastructure org provides developer environments, cloud infrastructure, and ML/AI GPU platforms for AV research and development teams to build, test, and run faster in GM.
In the employer’s words · Read in context
Posting record
Report an errorOpen 6 monthsWe first saw this posting 198 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 24, 2026198 days ago
- Recorded sightings
- 265
- Last seen by us
- Nov 8, 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
Time since we first saw it
Day 198
Up longer than most. Similar jobs usually come down between day 7 and day 72.
Well past General Motors’s usual: its jobs come down by about day 14.
From 4,645 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
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.
- Python
- AWS
- Azure
- BigQuery
- GCP
- Grafana
- Kubernetes
- Hugging Face
- PyTorch
Where the posting names them
- Education: Bachelor’s Degree in Computer Science, a related technical field, or equivalent practical experience. - Software Proficiency: Expert-level coding skills in Python and the ability to architect/debug within the PyTorch ecosystem. - Systems Engineering: Proven track record of resolving performance issues within large-scale distributed production environments.
- GPU Monitoring: Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability. - Cloud Platforms: Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure). -
- Model Deployment: Experience deploying and scaling open-source models via the Hugging Face ecosystem. - Data Analytics: Proficiency in BigQuery for large-scale data analysis and reporting. - Profiling Tools: Practical experience utilizing Nvidia Nsight and Nsight Compute for kernel-level performance tuning.
- Containerization: Hands-on experience with Kubernetes for orchestrating complex workloads. - GPU Monitoring: Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability. - Cloud Platforms: Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure).
- Architectural Knowledge: Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC). - Containerization: Hands-on experience with Kubernetes for orchestrating complex workloads. - GPU Monitoring: Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability.
- Hardware Expertise: Working knowledge of Enterprise-grade Nvidia GPU architectures, including H100, B200, and GB200. - Model Deployment: Experience deploying and scaling open-source models via the Hugging Face ecosystem. - Data Analytics: Proficiency in BigQuery for large-scale data analysis and reporting.
Your next step
Complete your application on generalmotors.wd5.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
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.
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
Job Description
About Us:
The AV Infrastructure org provides developer environments, cloud infrastructure, and ML/AI GPU platforms for AV research and development teams to build, test, and run faster in GM.
The Role:
GM is looking for a Senior Performance Engineer to join the AV Capacity and Performance Engineering team in the AV Infrastructure org to support our critical efforts in developing autonomous vehicles. The mission of the AVCPE team is to provide input into large scale ML infrastructure strategy, advise on key decisions affecting our cloud budget, identify and execute optimization projects, and provide capacity planning and engineering expertise to support GM’s efforts in developing autonomous vehicles (AV).
What you’ll be doing (Responsibilities)
Strategic Infrastructure Development: Adopt and run AV models to support GM’s long-term GPU system strategy and "evergreen" infrastructure roadmap.
Performance Optimization: Conduct deep-dive analyses of production workloads to identify bottlenecks and propose high-impact optimization strategies.
Cross-Functional Collaboration: Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors to spearhead projects that enhance engineering velocity and cost-efficiency.
Proactive System Scaling: Identify opportunities for architectural improvements to ensure the scalability and reliability of large-scale ML training and inference environments.
Your skills & abilities (Required Qualifications)
Experience: 5+ years of professional experience in high-scale infrastructure or ML systems.
Education: Bachelor’s Degree in Computer Science, a related technical field, or equivalent practical experience.
Software Proficiency: Expert-level coding skills in Python and the ability to architect/debug within the PyTorch ecosystem.
Systems Engineering: Proven track record of resolving performance issues within large-scale distributed production environments.
Architectural Knowledge: Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC).
Containerization: Hands-on experience with Kubernetes for orchestrating complex workloads.
GPU Monitoring: Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability.
Cloud Platforms: Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure).
What will give you a competitive edge (Preferred Qualifications)
Advanced Experience: 8+ years of relevant industry experience.
Hardware Expertise: Working knowledge of Enterprise-grade Nvidia GPU architectures, including H100, B200, and GB200.
Model Deployment: Experience deploying and scaling open-source models via the Hugging Face ecosystem.
Data Analytics: Proficiency in BigQuery for large-scale data analysis and reporting.
Profiling Tools: Practical experience utilizing Nvidia Nsight and Nsight Compute for kernel-level performance tuning.
Soft Skills: Strong technical communication skills with the ability to translate complex infrastructure needs into actionable business insights.
Hybrid: This role is categorized as Hybrid. This means the successful candidate is expected to report to Sunnyvale Technical Center at minimum three days per week or at the hiring manager’s discretion. Ability to sit remote in Seattle, WA until office opens.
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 $144,700 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: 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.
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- 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 $144,700 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.
- Location & working pattern
Sunnyvale, California, United States of America
- Soft Skills: Strong technical communication skills with the ability to translate complex infrastructure needs into actionable business insights. Hybrid: This role is categorized as Hybrid. This means the successful candidate is expected to report to Sunnyvale Technical Center at minimum three days per week or at the hiring manager’s discretion. Ability to sit remote in Seattle, WA until office opens. 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.
- 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.