Senior ML Infrastructure Engineer (Compute)

About this role

Job Description About the Team:  

The   AI Validation Platform  team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM’s AV efforts.   We’re   proud to serve as the   infrastructure   platform for teams developing autonomous vehicles (L3/L4/L5). Our platform supports the simulated validation of   state-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 high   utilization   of   cutting-edge   GPUs, 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, and   demon strate   a bias for action .    

You will play a key role in shaping the architecture, roadmap, and   user experience   of a robust service supporting   our   AI Validation / Simulation needs . The ideal candidate brings experience in designing distributed systems ,   strong problem-solving skills, and a   get-it-done attitude . This is a high-impact opportunity to influence the future of AI infrastructure at GM.  

What   you’ll   be 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 initiatives   a cross GM’s ML infrastructure.   

• Raise the engineering bar through technical leadership and by   establishing   best practices .    

At a Minimum We'd Like You   To   Have  

• 4+ years of industry experience, with a focus on high performance backend services.   

• Strong   expertise   in Go, or other similar coding languages.   

• Experience working with cloud platforms such as GCP, Azure, or AWS.   

• Experience   in   delivering   cross-functional initiatives.   

• Strong communication   skills and a proven ability to drive cross-functional initiatives.   

• Ability to thrive in a dynamic, multi-tasking environment with ever-evolving priorities.  

It's   Preferred 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?  

If   you’re   excited to tackle some of today’s most complex engineering challenges, see the impact of your work   in   real-world AV applications, and help shape the future of AI infrastructure at GM—this is the team for you.

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 $155,420 to $205,900. 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.  

Benefits:    • 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.  

Relocation:  This job may be eligible for relocation benefits.   Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Mountain View, you are expected to report to that location three times a week, at minimum.  





 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 workplac

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