2027 Summer Intern

About the Role

The Waymo AI Foundations team develops machine learning solutions for autonomous driving. We focus on areas including reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. As an intern, you will partner with industry leaders on impactful projects.

Key Responsibilities

• Literature research of SOTA in RSI, physics AI foundational models, autonomous driving foundational models, and World Action models.
• Connect SOTA research to projects to improve driver quality.
• Design new data and post-training recipes for RL the driver with a critic model and world model in a close loop setup.
• Coding and implementing the RSI system.
• Inspect training results and ablation studies to iterate algorithm design.

Requirements & Tech Stack

• Currently pursuing a PhD in Computer Science, Robotics, Machine Learning, or a related quantitative field.
• Depth in foundational AI model post-training, especially RL.
• Fluency in using AI coding agents.
• Fluency in one of the RL training frameworks such as Rex, Verl, or NeMo-RL.
• Fluency in AI model training basics such as transformer architecture, hyperparameter tuning, and overfitting debug.
• Familiarity with autonomous driving, physics AI, VLA, or world models.

Preferred Qualifications

• Depth in RL for robotics or autonomous driving models.
• Depth in world action models or video generation models.
• Experience in Recursive Self-Improvement training for AI models.

Note: This will be a hybrid onsite internship position.