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Senior Machine Learning Engineer - ML Training Infrastructure
General Motors
Full-time
Oklahoma City, OK
other-general
Posted:
June 09, 2026
Location:
Oklahoma City, OK, United States
Job Description
**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.
+ Model training performance analysis and optimization solutions to scale distributed training workflows and maximize resource utilization across heterogeneous hardware environme...
**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 environme...
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Apply Now Save for LaterJob Overview
Job Type:
Full-time
Location:
Oklahoma City, United States
Posted:
June 09, 2026
Deadline:
June 18, 2026