Senior ML Infrastructure Engineer - Embodied AI Scaling Foundations
AI summary of the role
Senior ML Infrastructure Engineer on the Embodied AI Infra Foundation team at GM, building scalable platforms and tools that power machine learning model training and evaluation for autonomous driving.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM.
- Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs.
- Take a holistic view of projects, considering their impact across multiple teams, and proactively drive technical prioritization.
- Collaborate closely with partner teams to ensure maximum benefit from the systems we build.
What you’ll bring
- 3+ years of experience building large-scale distributed systems/applications or advanced ML Applications.
- Proven track record of building robust frameworks with high-quality, long-lasting APIs.
- Deep understanding and practical experience with machine learning algorithms.
- Expertise in building reliable, highly performant, and cost-efficient systems leveraging modern cloud infrastructure.
Technologies
Docker · Kubernetes · Python · C++ · PyTorch · TensorFlow · Bazel · Buck · Blaze · Cmake
About General Motors
Global automaker selling Chevrolet, GMC, Cadillac, and Buick vehicles, plus financing and connected services, while shifting into EVs and driver assistance.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
to state-of-the-art optimization, our work is at the heart of our mission. About the team: Our goal is simple: dramatically accelerate the machine learning development cycle, freeing our engineers to focus entirely on enhancing the safety and performance of the car, rather than managing infrastructure. We are committed to delivering products that are performant, easy to use, and exceptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust systems to build the world's most advanced driverless vehicles. As a Senior ML Infra Engineer, you will build critical infrastructure that powers every machine learning engineer working on our cutting-edge Autonomous Driving models. From foundational models to state-of-the-art optimization, our goal is simple: dramatically accelerate the machine learning development cycle. We are committed to
More from the job description
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Role Overview: Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI Infra Foundation team at General Motors, where we build the critical infrastructure that powers every machine learning engineer working on our cutting-edge Autonomous Driving models. From foundational models to state-of-the-art optimization, our work is at the heart of our mission. About the team: Our goal is simple: dramatically accelerate the machine learning development cycle, freeing our engineers to focus entirely on enhancing the safety and performance of the car, rather than managing infrastructure. We are committed to delivering products that are performant, easy to use, and exceptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust syst [... source excerpt omitted ...] eptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust systems to build the world's most advanced driverless vehicles. What you'll do: Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM. Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality. Take a holistic view of projects, considering their impact across multiple teams, and proactively drive technical prioritization. Collaborate clos [... source excerpt omitted ...] nterviewing with high, well-calibrated standards, and play an essential role in recruiting. Mentor and onboard junior engineers and interns, helping them grow their careers. What you'll bring: 3+ years of experience building large-scale distributed systems/applications or advanced ML Applications. Proven track record of building robust frameworks with high-quality, long-lasting APIs. Deep understanding and practical experience with machine learning algorithms. Expertise in building reliable, highly performant, and cost-efficient systems leveraging modern cloud infrastructure. Hands-on experience with the entire ML development lifecycle and MLOps practices. Demonstrated a
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