Staff ML Engineer, ML Compute Platform

Hybrid This role is categorized as 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. 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 support autonomous vehicle development (L3/L4/L5) and other AI-driven products, enabling rapid innovation by optimizing for high-priority ML use cases. Our platform facilitates training and deployment of state-of-the-art models with a focus on performance, availability, concurrency, and scalability. We aim to maximize 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 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 role influencing the future of AI infrastructure at GM.You will help shape the user-facing experience of the platform, enabling ML practitioners to discover, schedule, and debug jobs easily. The ideal candidate has experience designing distributed systems for ML, strong problem-solving skills, and a product mindset focused on usability and reliability.What you’ll be doing:Design and implement core platform backend software componentsExperience with cloud platforms like GCP, Azure, or on-premises environmentsCollaborate with ML engineers and researchers to improve platform usability and address pain pointsOperate effectively in a dynamic, multi-tasking environment with evolving prioritiesAnalyze and enhance efficiency, scalability, and stability of system resourcesLead large-scale technical initiatives within GM’s ML ecosystemContribute to and potentially lead open source projects; represent GM in relevant communities #J-18808-Ljbffr

Created: 2025-09-21