Senior Machine Learning Engineer - ML Training Infrastructure

Job Description

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.

• 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 experience

• 5+ years professional software engineering experience.

• 1+ 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):

• 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 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