Work Arrangement:  

Hybrid: This internship is categorized as hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team. 

About the Role:   

As a Simulation Test Engineering AI/ML Software Engineer intern, you’ll partner with senior engineers to develop, evaluate, and deploy AI/ML tools to scale the development of end-to-end simulation tests, which are used by GM for validation of the autonomous driving software stack. You’ll learn about how simulation testing is performed at GM to evaluate AV stack performance, and your work will play a critical role in managing the creation and quality of these simulation tests throughout their lifecycle.  

About the Team:  

The GM AV Simulation team builds world-class testing and analysis related products and technologies to enable GM to accelerate 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 build the craziest 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:  

• Quickly ramp up on assigned codebase, product area, and/or system. 

• Meet with the cross-functional stakeholders working on code in your assigned area. 

• 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. 

• Complete assigned tasks efficiently with few iterations. 

• 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. 

• Participate in code reviews, technical discussions, and design reviews. 

• Collaborate with cross-functional teams to ensure seamless software integration. 

• Communicate effectively across multiple stakeholders. 

Required Qualifications:  

• Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field. 

• Solid understanding of modern machine learning techniques 

• Demonstrated coursework, research, or projects in AI/ML. 

• Strong programming skills in Python. 

• Able to work fulltime, 40 hours per week. 

Preferred Qualifications:  

• 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. 

• Interest in contributing to publications, open-source projects, or patents. 

• Familiarity with systems programming languages (e.g., C++ or Java) is a plus. 

• Intent to return to degree-program after the completion of the internship. 

Compensation:  

• The monthly salary for this role is $12,300 per month  

• GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program. 

What you’ll get from us (Benefits):  

• Paid US GM Holidays 

• GM Family First Vehicle Discount Program 

• Result-based potential for growth within GM 

• Intern events to network with company leaders and peers