2027 Summer Intern, PhD, Research, AV Planning

Highlights

• Design LLM meta-agents that generate and refine rewards for driving planners.
• Diagnose policy failures and reward trade-offs to improve autonomous planning.
• Help advance the Waymo Driver operating in dozens of cities and conditions.

What they offer

• Eligible to participate in generous benefits programs subject to eligibility requirements

Ideal candidate

A curious PhD researcher who loves tackling open-ended autonomy problems independently and translating exploratory ideas into real-world driving impact. Motivated by rigorous evaluation and sharing findings with the research community.

Requirements

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