Senior Machine Learning Engineer - ML Training Infrastructure

Job DescriptionThe 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.Raise the bar on system observability, debuggability, and operational excellence, and user experience.Model training performance analysis and optimization solutions to scale distributed training workflows and maximize resource utilization across heterogeneous hardware environments, and save cost.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 experience5+ years professional software engineering experience.1+ years specialized experience in AI/ML infrastructure, e.g., enabling distributed training for scaling large ML modelsStrong programming skills in Python, with proficiency in frameworks such as,PyTorch (preferred), TensorFlow, or similarExperience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure).Willingness to travel to Sunnyvale, CA as neededComfortable working in highly ambiguous and dynamic environmentsWhat Will Give You a Competitive Edge (preferred qualifications):Self-motivated, strong execution, impact-delivering orientedExtensive knowledge and experience with PyTorch 2.x+ and distributed training frameworkExperience with design and development of training framework that supports FSDP, Pipeline Parallelism and other scalable solutions to training large foundational modelsExperience with profiling, analysis, debugging and optimizing training and data loading performance.Excellent communication skills to resolve controversial, make consensus, communicate risks and give constructive feedbackCompensation: 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 New York, Colorado, California, or Washington.  The salary range for this role: is $170,000 to $240,800. 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. 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. This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. The selected candidate will be required to travel