Note: The job is a remote job and is open to candidates in USA. General Motors is redefining mobility and is seeking a Staff ML Infrastructure Engineer to join their Embodied AI team. In this role, you will develop and deploy machine learning solutions to support safe and reliable autonomous vehicle behavior, driving the development of core systems for rapid dataset generation and model training.
Responsibilities
- 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 across a longer timeline
- Proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build
- Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting
- Mentor and onboard junior engineers and interns, helping them grow their careers
Skills
- 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems
- Proven track record of designing robust frameworks with high-quality, durable APIs
- Deep understanding of machine learning algorithms with hands-on application
- Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure
- End-to-end experience across the ML development lifecycle, including MLOps practices
- Strong cross functional collaboration skills across teams and organizations
- Exceptional coding skills in Python or C++
- Strong interest in autonomous driving and its transformative potential
- BS, MS, or PhD in Computer Science, Mathematics, or equivalent practical experience
- Experience with distributed training methodologies
- Experience scaling ML training across large GPU/CPU clusters or other accelerators
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow)
- Experience with performance profiling and state-of-the-art training optimization techniques, including their impact on model performance
- Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake)
- Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes)
Benefits
- An incentive pay program offers payouts based on company performance, job level, and individual performance.
- 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 job may be eligible for relocation benefits.
- Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.
- Program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
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