The opportunity
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to…
What you'll do
Participate in Waymo’s Foundation World Model post-training and evaluation
Research and develop cutting edge RL and Distillation techniques for Autonomous Vehicle Trajectory Planning
Integrate emerging research from the broader AI community into Waymo’s: internal RL infrastructure, conducting rigorous ablations to identify and scale the most promising methods
Partner with engineering and research teams across Waymo to share recipes,: techniques, and post-training best practices to accelerate our collective know-how
PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar: technical field; with 3+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models
Demonstration of original contributions to the field through high-impact: publications (ArXiv, peer-reviewed conferences like NeurIPS/ICLR/CVPR), technical blog posts, or significant open-source contributions
What they're looking for
- Proficiency in implementing model training flows in a scalable, distributed: and performant manner such as Data parallel, FSDP and other sharding approaches
- A willingness to work with complexity of globally distributed inference infrastructure
- PhD in Computer Science, Machine Learning, or Robotics, with a research focus: on Reinforcement Learning, Foundation Models, or Multi-Modal learning
- Extensive experience designing and deploying Reinforcement Learning: infrastructure, specifically for on-policy learning or alignment with human preferences