RL Research Scientist - Autonomous Planning & World Models

Waymo; San Francisco (CA); On-site; USD 204,000 - 259,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid time off

Job summary

Waymo, a leader in autonomous driving, invites applications for a Senior Scientist role in the AI Foundations team. In this hybrid role you will report to a Principal Scientist and collaborate across research and engineering to advance RL and foundation models for autonomous vehicle trajectory planning.

You will contribute to world model post‑training, publish high‑impact work, and help scale training and inference on distributed infrastructure.

Qualifications

• PhD or Masters in Computer Science, Machine Learning, Robotics, or similar field with 3+ years of RL or Foundation Models experience.
• Demonstrated high‑impact publications (ArXiv, NeurIPS/ICLR/CVPR) or significant open‑source contributions.
• Proficiency in implementing scalable training flows and distributed inference infrastructure.

Responsibilities

• Participate in Waymo’s Foundation World Model post‑training and evaluation.
• Research and develop RL and Distillation techniques for Autonomous Vehicle Trajectory Planning.
• Integrate research into Waymo’s RL infrastructure and run rigorous ablations to identify scalable methods.
• Collaborate with engineering and research teams to share recipes and best practices.

Skills

Reinforcement Learning

Foundation Models

Distributed training

Publications

Inference infrastructure

Model training flows

Education

PhD in CS

Masters in CS/ML/Robotics

Job description

Waymo, a leader in autonomous driving, invites applications for a Senior Scientist role in the AI Foundations team. In this hybrid role you will report to a Principal Scientist and collaborate across research and engineering to advance RL and foundation models for autonomous vehicle trajectory planning.

You will contribute to world model post‑training, publish high‑impact work, and help scale training and inference on distributed infrastructure.