Job Description

Hybrid This role is categorized as hybrid. This means the successful candidate is expected to report to the GM Global Technical Center - Cole Engineering Center Podium or Mountain View Technical Center , CA at least three times per week, at minimum or other frequency dictated by the business. This job is eligible for relocation assistance.

About the Team:

The ML Compute Platform is part of the AI Compute Platform organization within Infrastructure Platforms. Our team owns the cloud-agnostic, reliable, and cost-efficient compute backend that powers GM AI. We’re proud to serve as the AI infrastructure platform for teams developing autonomous vehicles (L3/L4/L5), as well as other groups building AI-driven products for GM and its customers. We enable rapid innovation and feature development by optimizing for high-priority, ML-centric use cases. Our platform supports the training and deployment of state-of-the-art (SOTA) machine learning models with a focus on performance, availability, concurrency, and scalability. We’re committed to maximizing GPU utilization across platforms (B200, H100, A100, and more) while maintaining reliability and cost efficiency.

About the Role:

We are seeking a Staff ML Engineer to help build and scale robust compute platforms for ML workflows. In this role, you’ll work closely with ML engineers and researchers to ensure efficient model training and seamless deployment into production. This is a high-impact opportunity to influence the future of AI infrastructure at GM.

You will play a key role in shaping the user-facing experience of the platform, ensuring that ML practitioners can discover, schedule, and debug jobs with ease. The ideal candidate brings experience in designing distributed systems for ML, strong problem-solving skills, and a product mindset focused on platform usability and reliability.

What you’ll be doing:

Design and implement core platform backend software componentsExperience cloud platforms like GCP, Azure or on-premCollaborate with ML engineers and researchers to understand platform pain points and improve developer experienceThrive in a dynamic, multi-tasking environment with ever-evolving priorities. Interface with other teams to incorporate their innovations and vice versaAnalyze and improve efficiency, scalability, and stability of various system resourcesLead large-scale technical initiatives across GM’s ML ecosystemHelp raise the engineering bar through technical leadership and best practicesContribute to and potentially lead open source projects; represent GM in relevant communities

 



Additional Job Description

​Requirements

8+ years of industry experienceExpertise in either Go, C++, Python or other relevant coding languagesStrong background with kubernetes at scaleRelevant experience building large-scale with distributed systemsExperience leading and driving large scale initiativesExperience working with Google Cloud Platform, Microsoft Azure, or Amazon Web Services

Preferred Qualifications

Hands-on experience building ML infrastructure platforms with strong developer/user experienceExperience working with or designing job orchestration interfaces, CLI tools, or web UIs for ML workflowsFamiliarity with observability, telemetry, and user feedback loops to inform product improvementsExperience with GPU/TPU optimizationsExperience with training frameworks like PyTorch, TorchXExperience with Ray frameworkLeadership/active participation in the open source communityExperience infrastructure applications or similar experience

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

Compensation: The expected base compensation for this role is: $195,000 - $298,000 Actual base compensation within the identified 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.

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Benefits Overview

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