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Senior Machine Learning Engineer - ML Training Infrastructure
General MotorsDover
Job OverviewSenior ML Engineer – ML Training Infrastructure, General Motors. We are seeking an experienced, technical‑oriented, impact‑delivering expert in ML training infrastructure to design and bui
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Senior Machine Learning Engineer - ML Training Infrastructure
- Dover, Delaware, United States
- Dover, Delaware, United States
Über
Senior ML Engineer – ML Training Infrastructure, General Motors. We are seeking an experienced, technical‑oriented, impact‑delivering expert in ML training infrastructure to design and build scalable, reliable, high‑performance AI/ML platform infrastructure to support advanced AI research and model development initiatives across General Motors vehicles. Responsibilities
Design and develop scalable, reliable, high-performance ML framework to support model training at scale. Perform model training performance analysis and optimization to scale distributed training workflows and maximize resource utilization across heterogeneous hardware environments, reducing costs. Raise the bar on system observability, debuggability, operational excellence, and user experience. Collaborate with cross‑functional teams to integrate new features and technologies into the platform. Required Qualifications
Bachelor’s 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) or TensorFlow. 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. Preferred Qualifications
5+ years professional software engineering experience. Self‑motivated, strong execution, impact‑delivering orientation. Extensive knowledge and experience with PyTorch 2.x+ and distributed training frameworks. Experience designing and developing training frameworks that support FSDP, Pipeline Parallelism, and other scalable solutions for large foundational models. Experience with profiling, analysis, debugging, and optimizing training and data loading performance. Excellent communication skills for resolving controversies, building consensus, communicating risks, and giving constructive feedback. Compensation
The salary range for this role is $170,000 to $240,000. The actual base salary offered within this range will vary based on factors relevant to the position. An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits
Medical, dental, vision, Health Savings Account, Flexible Spending Accounts. Retirement savings plan. Sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance programs. Employee assistance program, GM vehicle discounts, and more. Relocation & Travel
This role is based remotely. Candidates living within a specific mile radius of a GM hub may be expected to report to the location three times a week. Selected candidates will be required to travel less than 25% of the time and may travel to Sunnyvale, CA as needed. Equal Employment Opportunity
General Motors is committed to a workplace that is free of unlawful discrimination. 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, veteran status, or any other protected status in accordance with federal, state, and local laws.
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- English
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