Senior ML Accelerator Engineer - GPU

Job DescriptionAbout the Mission GM’s vision of Zero Crashes, Zero Emissions, and Zero Congestion guides everything we do in autonomous and assisted driving. The AV organization is building advanced automated driving technologies, including Level 4–capable fully self-driving systems, to move us toward safer, more sustainable, and more accessible mobility. For the AI Kernels & Compilers team, that mission shows up in the details: turning cutting‑edge perception, prediction, and planning research into production‑grade software that can run efficiently and reliably on real vehicles at scale. We pioneer new approaches to model export, kernel development, and performance engineering so that every cycle on our accelerators translates into better situational awareness, faster reaction times, and more robust behavior on the road. If you want your compiler and kernels work to directly influence how automated vehicles understand and react to the world — while operating at the safety, reliability and scale of a company like GM — this is where that impact becomes real. About the Team The AI Kernels team builds high‑performance GPU kernels and custom libraries that sit at the heart of our on‑vehicle ML inference for ADAS and autonomous driving. We own making core AI workloads faster, more reliable, and easier to maintain and deploy on real cars, under real‑world constraints. That means: Designing and implementing custom operators when vendor libraries hit their limits Integrating those kernels deep into our ML runtime stack Debugging and tuning GPU performance across the AV software stack, often on hardware‑in‑the‑loop We partner closely with AI Solutions, AI Compilers, AI Architecture, and AI Tooling to ensure models deploy efficiently to the car while consistently meeting strict latency, throughput, and reliability targets. If you enjoy pushing GPUs to their limits and seeing your work directly impact how autonomous vehicles perceive and act in the world, this is the team for you. What you’ll be doing (Responsibilities) Design, implement, benchmark, and iterate on CUDA-based kernels and custom operators to squeeze every last drop of performance out of on-vehicle inference workloads. Build and improve tooling and infrastructure that make it easier to profile, debug, and validate CUDA kernels and accelerator-backend code across the AV stack. Partner with AI Solutions, Compilers, and Architecture to translate model and system requirements into concrete kernel roadmaps, priorities, and project plans. Collaborate with cross-functional teams (compiler, performance tooling, runtime, deployment solutions) to deliver reusable, reliable, high-performance libraries into production. Maintain high technology standards, methodologies, processes, and guidelines for GPU kernel development and performance engineering through code review. Manage relationships with internal customers to ensure our kernels and libraries meet real-world needs Your Skills & Abilities (Required Qualifications) Minimum 2+ years of relevant industry experience or equivalent experience BS, MS or PhD in CS, or related technical field Excellent GPU programming skills in CUDA, with a thorough understanding of parallel programming patterns and GPU architecture. Hands-on experience benchmarking, profiling, debugging and optimizing accelerator libraries and kernels to extract optimal performance using the NSight suite of tools or similar. Strong background in software architecture, library design, and design patterns. Strong C++ programming skills with the ability to feel comfortable in large codebases. Solid background in system performance, high performance computing and/or architecture-aware optimizations. Strong communication skills and the ability to work collaboratively within a team Excellent analytical and problem-solving skills What Will Give You A Competitive Edge (Preferred Qualifications) 2+ years of relevant industry experience or equivalent experience Experience with tensor core programming, CUTLASS and/or CuTe Experience with ML model architectures, in particular transformer-based Experience with low latency or real time systems Experience with lower levels of an accelerator software stack (i.e. drivers, runtimes, and compilers) 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 $170,100 to $258,300. 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. 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}. The selected candidate will be required to travel <25% for this role. This job may be eligible for relocation benefits. 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.Why Join UsWe 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 OverviewFrom 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.AccommodationsGeneral 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, emailus or call us at View phone number on click.appcast.io. 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.SummaryLocation: Sunnyvale, California, United States of America; Remote - Washington; Austin, Texas, United States of America; San Francisco, California, United States of America; Warren, Michigan, United States of AmericaType: Full time