To develop, evaluate, and deploy AI/ML tools to scale the development of end-to-end simulation tests for validation of the autonomous driving software stack at General Motors
Requirements
- Solid understanding of modern machine learning techniques
- Demonstrated coursework, research, or projects in AI/ML
- Strong programming skills in Python
- Exposure to deep learning architectures such as Transformers, CNNs, or Diffusion Models
- Hands-on experience with one or more machine learning frameworks (e.g., PyTorch, TensorFlow, JAX, or Keras)
- Experience with robotics, computer vision through projects or research
- Familiarity with multimodal learning or working with sensor data
Responsibilities
- Quickly ramp up on assigned codebase, product area, and/or system
- Develop data pipelines to curate inputs, manage ground truth, and aggregate results across large experiment runs
- Build validation metrics that produce clear pass/fail signals and confidence intervals for ML model behavior in simulation
- Enhance AI/ML validation frameworks and tools for autonomous vehicle software systems
- Leverage vision-language models (VLMs) and large language models (LLMs) to classify autonomy performance, mine critical scenarios, and prioritize validation efforts, integrating human-in-the-loop where appropriate
- Develop, test, and deploy production-ready code across components of our simulation infrastructure
- Identify problem statements, outline optimal solutions, account for tradeoffs and edge cases
Other
- Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field
- Able to work fulltime, 40 hours per week
- Intent to return to degree-program after the completion of the internship
- Meet with the cross-functional stakeholders working on code in your assigned area
- Communicate effectively across multiple stakeholders
