Senior Machine Learning Engineer - ML Training Infrastructure
General Motors · Sunnyvale, California, United States of America ·
- Seniority
- Senior
- Category
- ML ai
- Experience
- 1+ years
- Company size
- 1000+
- Salary
- USD 170,000 – 240,800 / year
General Motors · Sunnyvale, California, United States of America ·
Faculty AI · London
Faculty AI · London
Scale AI · Denver, CO; Honolulu, HI; Washington, DC
The Senior Machine Learning Engineer will design and build scalable AI/ML platform infrastructure to support distributed model training for intelligent driving technologies. The role involves optimizing training performance and collaborating with research teams using Python, PyTorch, and cloud-based distributed computing environments.
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.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
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Non-Discrimination and Equal Employment Opportunities (U.S.)
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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
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