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 pre-training and post-training by owning the data recipe
Invest in data best practices: best practices around clustering, filtering, de-duplication, long-tail data mining, memorization, etc. Also help lead a team of research engineers to build the data flywheel to enable the above from Waymo’s massive driving data
Integrate emerging research from the broader community to do rigorous: ablations and promising data research techniques. Focus on managing a team of scientists that would work on scaling ladders for pre-training, data mix optimizations and RL recipes (preferences) for post-training.
Engage with the wider research community on best practices around data: centric evaluation creation and refinement
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 5+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models
What they're looking for
- 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
- Experience leading teams of research scientists and engineers to deploy real: world impact in AI - including showing real world impact. Ability to be hands-on when needed to adapt models as and when needed.
- Extensive experience working with data and recipes for large scale foundation models
- PhD in Computer Science, Machine Learning, or Robotics, with a research focus: on Data centric AI, Reinforcement Learning, Foundation Models, or Multimodal learning