2027 Summer Intern - AI/ML Engineer, Autonomous Vehicle: Simulation
- Compensation
- Not disclosed
- Location
- Sunnyvale, California, United States of America
- Work setup
- Not specified
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Currently pursuing a Bachelor's Degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Must have at least one additional quarter/semester of school remaining following the completion of the internship
- Solid understanding of modern machine learning techniques
- Demonstrated coursework, research, or projects in AI/ML.
- Strong programming skills in Python.
- Able to work full-time, 40 hours per week.
Nice to have
- Candidates are not expected to meet every qualification listed below. Depending on the needs of a specific Autonomous Vehicles team, a combination of these skills and areas of knowledge may be relevan
- Currently pursuing a master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Exposure to deep learning architectures such as Transformers, CNNs, or diffusion models.
- Hands-on experience with one or more machine learning frameworks, such as PyTorch, TensorFlow, JAX, or Keras.
- Background in robotics and computer vision gained through projects or research.
- Familiarity with multimodal learning or working with sensor data.
- Interest in contributing to publications, open-source projects, or patents.
- Knowledge of systems programming languages, such as C++ or Java, is a plus.
- Intent to return to a degree program after completing the internship.
Full description
Job Description
About the role:
As a Simulation AI/ML Engineer intern, you’ll partner with senior engineers to deliver key components of the evaluation strategy for GM’s autonomous vehicle programs. In this role, you will scale the testing and evaluation of our self-driving stack by applying AI/ML techniques to software solutions. You will design, perform experiments, and deploy these solutions as production-ready code. The work you do will be directly applied to the iteration and validation of the self-driving stack.
About the team:
The GM AV Simulation team builds world-class testing and analysis related products and technologies to enable GM to accelerate the development of autonomous vehicles as well as general vehicle software development. Our customers range from AV developers understanding the effects of their code on vehicle behavior, data engineers using our data pipelines to generate meaningful insights for various evaluation needs, to the release team tracking top-line performance metrics on releases. AV Simulation aims to deliver intuitive user experiences for robotics and AI engineers that accelerate GM towards a driverless future.
What you’ll do:
- Leverage AI/ML techniques to scale testing, classify autonomy performance, and mine critical scenarios, integrating human-in-the-loop where appropriate.
- Collaborate with engineers to integrate ML models into simulation tests and evaluation pipelines.
- Ramp up quickly on the codebase and domain; deliver assigned tasks efficiently with few iterations.
- Develop, test, and deploy production-ready code across components of our simulation infrastructure.
- Define problem statements and implement optimal, tradeoff-aware solutions that cover edge cases.
- Collaborate with cross-functional stakeholders, contribute to design and code reviews, and ensure seamless integration through clear communication.
Required Qualifications:
- Currently pursuing a Bachelor's Degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Must have at least one additional quarter/semester of school remaining following the completion of the internship
- Solid understanding of modern machine learning techniques
- Demonstrated coursework, research, or projects in AI/ML.
- Strong programming skills in Python.
- Able to work full-time, 40 hours per week.
Preferred Qualifications:
- Candidates are not expected to meet every qualification listed below. Depending on the needs of a specific Autonomous Vehicles team, a combination of these skills and areas of knowledge may be relevant.
- Currently pursuing a master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.