Simulation AI/ML Engineer Intern — AV Testing

General Motors LLC; Sunnyvale (CA); Hybrid; USD 90,000 - 107,000; Full time

Benefits offered by this job

Paid US GM Holidays

GM Family First

Vehicle Discount Program

Job summary

General Motors LLC is seeking a Simulation AI/ML Engineer intern to help scale the testing and evaluation of GM’s autonomous vehicle stack. You will partner with senior engineers to design experiments, implement production-ready code, and deliver components of the evaluation strategy for AV programs.

You will work in GM's AV Simulation team to build testing and analysis tools, collaborate with data engineers, and contribute to the release and validation of simulation pipelines.

Qualifications

• Pursuing a Bachelor's Degree in CS/AI/ML/Robotics or related STEM fields.
• Must have at least one additional quarter/semester remaining after internship.
• Solid understanding of modern machine learning techniques.
• Coursework, research or projects in AI/ML.

Responsibilities

• Apply AI/ML techniques to scale testing and classify autonomy performance.
• Collaborate with engineers to integrate ML models into simulation tests and evaluation pipelines.
• Ramp up quickly on the codebase and deliver tasks efficiently with few iterations.
• Develop, test, and deploy production-ready code across simulation infrastructure.
• Define problem statements and implement optimal, tradeoff-aware solutions covering edge cases.
• Collaborate with cross-functional stakeholders and participate in design and code reviews.

Skills

Python

ML techniques

AI/ML coursework

Education

Bachelor's degree in computer science, AI, ML, robotics, engineering or related STEM

Job description

General Motors LLC is seeking a Simulation AI/ML Engineer intern to help scale the testing and evaluation of GM’s autonomous vehicle stack. You will partner with senior engineers to design experiments, implement production-ready code, and deliver components of the evaluation strategy for AV programs.

You will work in GM's AV Simulation team to build testing and analysis tools, collaborate with data engineers, and contribute to the release and validation of simulation pipelines.