Staff Machine Learning Engineer - ML Training Infrastructure

Job Description The Role: We are seeking an experienced, technically strong, impact-driven expert in ML Training Infrastructure with a demonstrated ability to lead through hands-on technical work. In this role, you will be responsible for defining the technical direction and driving the design and development of scalable, reliable, and high-performance AI/ML platform infrastructure that enables advanced AI research and model development at scale. As a Staff ML Engineer, you will operate as a technical leader across initiatives, partnering closely with machine learning engineers, research scientists, and platform teams to shape architecture, drive major technical decisions, and deliver state-of-the-art AI infrastructure that enables the future of intelligent driving technologies across General Motors vehicles. What You'll Do: • Define and drive the architecture, design, and development of scalable, reliable, and high-performance ML frameworks and platform capabilities to support model training at scale. • Lead model training performance analysis and optimization efforts across distributed training workflows, improving scalability, efficiency, and cost across heterogeneous hardware environments. • Raise the bar on system observability, debuggability, operational excellence, and developer experience across the ML training stack. • Own large, ambiguous, cross-functional technical initiatives from strategy through execution, including technical roadmap definition, tradeoff analysis, and delivery. • Influence platform direction by identifying long-term infrastructure investments, setting engineering standards, and driving adoption of best practices across teams. • Collaborate across organizational boundaries to align requirements, resolve technical disagreements, and integrate new capabilities into the platform ecosystem. • Mentor engineers through design reviews, technical guidance, and hands-on partnership, while elevating engineering quality across the team. Your Skills & Abilities (Required Qualifications) • Bachelor's degree or higher in Computer Science or a related field, or equivalent practical experience. • 7+ years of professional software engineering experience. • 5+ years of specialized experience in AI/ML infrastructure, such as enabling distributed training for large-scale ML models. • Strong programming skills in Python, with deep proficiency in frameworks such as PyTorch (preferred), TensorFlow, or similar ML systems. • Proven experience designing and operating distributed systems for ML training, including distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure). • Demonstrated track record of leading technically ambiguous, cross-team infrastructure initiatives and driving them to measurable impact. • Strong architectural judgment and ability to make sound technical tradeoffs across performance, reliability, usability, and cost. • Willingness to travel to Sunnyvale, CA as needed. • Comfortable operating in highly ambiguous and dynamic environments. What Will Give You a Competitive Edge (preferred qualifications): • 7+ years of professional software engineering experience. • Deep expertise in PyTorch 2.x+ and distributed training frameworks. • Experience designing and developing training platforms that support FSDP, pipeline parallelism, and other scalable solutions for training large foundational models. • Experience profiling, analyzing, debugging, and optimizing training and data loading performance at scale. • Strong record of technical leadership through architecture reviews, roadmap influence, and cross-team execution. • Excellent communication skills, with the ability to build consensus, navigate controversial decisions, communicate risks clearly, and provide constructive technical feedback. • Self-motivated, execution-oriented, and motivated by delivering broad organizational impact. 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 the California Bay Area. • The salary range for this role is $185,000 to $335,300. The actual base salary a successful candidate will be offered within this 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. Relocation: This job may be eligible for relocation benefits. Benefits: • 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, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Company Vehicle: Upon successful completi...