2027 Summer Intern, PhD, Research, AV Planning

About the Role

Waymo is seeking a PhD intern for its AI Foundations team, focusing on machine learning solutions for autonomous driving. The role involves developing systems that use LLM meta-agents to generate, synthesize, and refine reward functions for autonomous driving planning policies.

Key Responsibilities

• Design, implement, and benchmark a system where LLM meta-agents generate, synthesize, and iteratively refine reward functions for autonomous driving planning policies.
• Diagnose policy failure modes, reward exploitation, and multi-objective trade-offs, integrating findings back into the automated discovery loop.
• Collaborate with scientists and engineers to transfer validated reward formulations and tooling into planner recipes.
• Document research outcomes, distill key design patterns, and prepare findings for internal tech transfers and potential conference publication.

Requirements & Tech Stack

• Currently pursuing a PhD in Computer Science, Robotics, Machine Learning, or a related quantitative field.
• Strong hands-on experience in Reinforcement Learning (RL / RLFT) and training deep learning policies with PyTorch or JAX.
• Demonstrated proficiency in Python and modern ML engineering practices.
• Familiarity with autonomous vehicle planning, trajectory optimization, or sequential decision-making under uncertainty.

Preferred Qualifications

• Track record of peer-reviewed publications at top AI/robotics conferences (e.g., NeurIPS, ICRA, IROS, CoRL, ICML, ICLR, CVPR).
• Experience with LLM-guided code generation, automated reward discovery (e.g., Eureka-like frameworks), or meta-RL methods.
• Hands-on experience with RL or RLFT training in LLM/VLM/robotics.
• Proven ability to independently drive an exploratory research problem from ideation to implementation and results.

This will be a hybrid onsite internship position.

The expected hourly rate is $85 USD.