Senior ML Infrastructure Engineer (Compute)

GM • Sunnyvale, CA

5h

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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 .

Benefits

• 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 .

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees