Senior Machine Learning Engineer

The Role: * We are seeking an experienced, technical oriented, impact delivering-driven expert in ML Training Infrastructure with a strong ability to execute hands-on technical work. In this role, you will be responsible for designing and building scalable, reliable, and high-performance AI/ML platform infrastructure to support advanced AI research and model development initiatives. As a Senior ML Engineer, you will collaborate closely with machine learning engineers, research scientists, and other partners to develop state-of-the-art AI solutions that enable the future of intelligent driving technologies across General Motors vehicles. What You'll Do: Design and development of scalable, reliable, high-performance ML framework to support model training at scale. Model training performance analysis and optimization solutions to scale distributed training workflows and maximize resource utilization across heterogeneous hardware environments, and save cost. Raise the bar on system observability, debuggability, and operational excellence, and user experience. Collaborate with cross-functional teams to integrate new features and technologies into the platform. Your Skills & Abilities (Required Qualifications) Bachelors degree or higher in Computer Science or equivalent major OR equivalent relevant experience 3+ years professional software engineering experience 2+ years specialized experience in AI/ML infrastructure, e.g., enabling distributed training for scaling large ML models Strong programming skills in Python, with proficiency in frameworks such as,PyTorch (preferred), TensorFlow, or similar Experience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure). Willingness to travel to Sunnyvale, CA as needed Comfortable working in highly ambiguous and dynamic environments What Will Give You a Competitive Edge (preferred qualifications): 5+ years of professional software engineering experience. Self-motivated, strong execution, impact-delivering oriented Extensive knowledge and experience with PyTorch 2.x+ and distributed training framework Experience with design and development of training framework that supports FSDP, Pipeline Parallelism and other scalable solutions to training large foundational models Experience with profiling, analysis, debugging and optimizing training and data loading performance. Excellent communication skills to resolve controversial, make consensus, communicate risks and give constructive feedback 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 $170,000 to $240,000. 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. #GM-AV-1 This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. The selected candidate will be required to travel