Staff ML Engineer, ML Compute Platform

Job Description 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 directed 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 a cloud‑agnostic, reliable, and cost‑efficient compute backend that powers GM AI. We support autonomous vehicle teams (L3/L4/L5) and other groups building AI‑driven products, enabling rapid innovation and feature development. We focus on training and deployment of state‑of‑the‑art machine learning models with emphasis on performance, availability, concurrency, and scalability, maximizing GPU utilization across platforms. 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, shaping the user‑facing experience of the platform. Responsibilities Design and implement core platform backend software components Work with cloud platforms such as GCP, Azure, or on‑prem infrastructure Collaborate with ML engineers and researchers to understand platform pain points and improve developer experience Navigate a dynamic, multi‑tasking environment with evolving priorities, interfacing with other teams to incorporate innovations Analyze and improve efficiency, scalability, and stability of system resources Lead large‑scale technical initiatives across GM’s ML ecosystem 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 coding languages Strong background with Kubernetes at scale Experience building large‑scale distributed systems Experience leading and driving large‑scale initiatives Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services Preferred Qualifications Hands‑on experience building ML infrastructure platforms focused on developer/user experience Experience designing 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 training frameworks such as PyTorch and TorchX Experience with the Ray framework Leadership or active participation in the open‑source community Experience with infrastructure applications or similar roles Benefits and Compensation Base compensation: $195,000 - $298,000 (dependent on factors relevant to the position) Bonus potential: incentive pay based on company performance, job level, and individual performance Benefits: health, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation and holidays Equal Employment Opportunity General Motors is committed to being a workplace that is not only free of unlawful discrimination but one that genuinely fosters inclusion and belonging. All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call View phone number on click.appcast.io. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position you are applying for. #J-18808-Ljbffr Dormont Manufacturing Company