General Motors
Overview
Join to apply for the
Staff ML Engineer, ML Compute Platform
role at
General Motors . This role is eligible for relocation assistance and is Hybrid. 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, or as dictated by the business. 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 support the training and deployment of state-of-the-art (SOTA) ML models with a focus on performance, availability, concurrency, and scalability, aiming to maximize GPU utilization across platforms (B200, H100, A100, and more) while maintaining reliability and cost efficiency. This team serves as the AI infrastructure platform for autonomous vehicles (L3/L4/L5) and other GM AI-driven products. About the Role
We are seeking a Staff ML Engineer to help build and scale robust compute platforms for ML workflows. You will 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 help shape the user-facing experience of the platform, ensuring ML practitioners can discover, schedule, and debug jobs with ease. The ideal candidate brings experience 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 components Experience with cloud platforms like GCP, Azure, or on-prem Collaborate with ML engineers and researchers to understand platform pain points and improve developer experience Thrive in a dynamic, multi-tasking environment with evolving priorities; interface with other teams to incorporate innovations Analyze and improve efficiency, scalability, and stability of various system resources Lead large-scale technical initiatives across GM’s ML ecosystem Help raise the engineering bar through technical leadership and best practices Contribute to and potentially lead open source projects; represent GM in relevant communities Requirements
8+ years of industry experience Expertise in Go, C++, Python, or other relevant languages Strong background with Kubernetes at scale Experience building large-scale distributed systems Experience leading and driving large-scale initiatives Experience working with Google Cloud Platform, Microsoft Azure, or Amazon Web Services Preferred Qualifications
Hands-on experience building ML infrastructure platforms with strong developer/user experience Experience with job orchestration interfaces, CLI tools, or web UIs for ML workflows Familiarity with observability, telemetry, and user feedback loops to inform product improvements Experience with GPU/TPU optimizations Experience with PyTorch, TorchX, and Ray framework Leadership or active participation in the open source community Experience with infrastructure applications or similar 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 AI applications, and help shape the future of AI infrastructure at GM, this is the team for you. Compensation and Benefits
Compensation: The expected base compensation for this role is $195,000 - $298,000. Actual base compensation varies 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 health and wellbeing benefits including medical, dental, vision, HSA/FSA, retirement savings, sickness and accident benefits, life insurance, paid vacations & holidays. About GM and Inclusion
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion. GM is committed to an inclusive workplace where everyone belongs. All employment decisions are made without regard to protected characteristics in accordance with applicable laws. We encourage applicants to review key responsibilities and qualifications for each role and apply for positions that match their skills. Accommodations are available for applicants with disabilities. If you need a reasonable accommodation, email or call us with details about the job title and requisition number. Accommodation
If you need a reasonable accommodation to assist with your job search or application, please email us or call 800-865-7580. Include the job title and requisition number in your message.
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Join to apply for the
Staff ML Engineer, ML Compute Platform
role at
General Motors . This role is eligible for relocation assistance and is Hybrid. 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, or as dictated by the business. 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 support the training and deployment of state-of-the-art (SOTA) ML models with a focus on performance, availability, concurrency, and scalability, aiming to maximize GPU utilization across platforms (B200, H100, A100, and more) while maintaining reliability and cost efficiency. This team serves as the AI infrastructure platform for autonomous vehicles (L3/L4/L5) and other GM AI-driven products. About the Role
We are seeking a Staff ML Engineer to help build and scale robust compute platforms for ML workflows. You will 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 help shape the user-facing experience of the platform, ensuring ML practitioners can discover, schedule, and debug jobs with ease. The ideal candidate brings experience 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 components Experience with cloud platforms like GCP, Azure, or on-prem Collaborate with ML engineers and researchers to understand platform pain points and improve developer experience Thrive in a dynamic, multi-tasking environment with evolving priorities; interface with other teams to incorporate innovations Analyze and improve efficiency, scalability, and stability of various system resources Lead large-scale technical initiatives across GM’s ML ecosystem Help raise the engineering bar through technical leadership and best practices Contribute to and potentially lead open source projects; represent GM in relevant communities Requirements
8+ years of industry experience Expertise in Go, C++, Python, or other relevant languages Strong background with Kubernetes at scale Experience building large-scale distributed systems Experience leading and driving large-scale initiatives Experience working with Google Cloud Platform, Microsoft Azure, or Amazon Web Services Preferred Qualifications
Hands-on experience building ML infrastructure platforms with strong developer/user experience Experience with job orchestration interfaces, CLI tools, or web UIs for ML workflows Familiarity with observability, telemetry, and user feedback loops to inform product improvements Experience with GPU/TPU optimizations Experience with PyTorch, TorchX, and Ray framework Leadership or active participation in the open source community Experience with infrastructure applications or similar 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 AI applications, and help shape the future of AI infrastructure at GM, this is the team for you. Compensation and Benefits
Compensation: The expected base compensation for this role is $195,000 - $298,000. Actual base compensation varies 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 health and wellbeing benefits including medical, dental, vision, HSA/FSA, retirement savings, sickness and accident benefits, life insurance, paid vacations & holidays. About GM and Inclusion
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion. GM is committed to an inclusive workplace where everyone belongs. All employment decisions are made without regard to protected characteristics in accordance with applicable laws. We encourage applicants to review key responsibilities and qualifications for each role and apply for positions that match their skills. Accommodations are available for applicants with disabilities. If you need a reasonable accommodation, email or call us with details about the job title and requisition number. Accommodation
If you need a reasonable accommodation to assist with your job search or application, please email us or call 800-865-7580. Include the job title and requisition number in your message.
#J-18808-Ljbffr