Senior ML Infrastructure Engineer (Compute)
Brief overview
About the company
Global automotive manufacturer focused on safe, sustainable mobility.
Visa sponsorship history
4 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.Job description
Job Description
About the Team:
TheAI Validation Platform team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM’s AV efforts.We’reproud to serve as theinfrastructureplatform for teams developing autonomous vehicles (L3/L4/L5). Our platform supports the simulated validation ofstate-of-the-art(SOTA) machine learning models, with a focus on performance, availability, concurrency, and scalability. We enable rapid innovation and development by prioritizing high-impact, ML-centric use cases.
About the Role:
We are seeking a Senior ML Infrastructure engineer to help build and scale robust Compute platforms for Simulation workflows. In this role, you will focus on scaling, driving efficiency, and highutilizationofcutting-edgeGPUs, while also leveling up the platform’s reliability. The successful candidate will have experience building and running scalable distributed systems.They will rapidly test and promote ideas, have strong problem-solving skills, anddemonstratea bias for action.
You will play a key role in shaping the architecture, roadmap, anduser experienceof a robust service supportingourAI Validation / Simulation needs. The ideal candidate brings experience in designing distributed systems,strong problem-solving skills, and aget-it-done attitude. This is a high-impact opportunity to influence the future of AI infrastructure at GM.
Whatyou’llbe doing:
Design and implement core platform backend software components.
Collaborate with Simulation engineers, ML engineers and researchers to understand critical workflows, parse them to platform requirements, and deliver incremental value.
Lead technical decision-making on Compute architecture, cloud capacity provisioning, caching, and auto-scaling mechanisms.
Drive the development of monitoring, observability, and metrics to ensure reliability, performance, and resource optimization.
Proactively research and integrate frameworks, hardware accelerators, and distributed computing techniques.
Lead large-scale technical initiativesacross GM’s ML infrastructure.
Raise the engineering bar through technical leadership and byestablishingbest practices.
At a Minimum We'd Like YouToHave
4+ years of industry experience, with a focus on high performance backend services.
Strongexpertisein Go, or other similar coding languages.
Experience working with cloud platforms such as GCP, Azure, or AWS.
Experienceindeliveringcross-functional initiatives.
Strong communicationskills and a proven ability to drive cross-functional initiatives.
Ability to thrive in a dynamic, multi-tasking environment with ever-evolving priorities.
It'sPreferred If You Have
Hands-on experience with Cloud VM services Google Compute Engine.
Experience with hardware-in-the-loop validation systems.
Experience with high performance computing (HPC).
Experience working with or designing interfaces and clients for developer workflows.
Familiarity with telemetry, and other feedback loops to inform product improvements.
Familiarity with hardware acceleration (GPUs) and optimizations.
Why Join Us?
Ifyou’reexcited to tackle some of today’s most complex engineering challenges, see the impact of your workinreal-world AV applications, and help shape the future of AI infrastructure at GM—this is the team for you.
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
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Non-Discrimination and Equal Employment Opportunities (U.S.)
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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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