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
Own the data recipe for Waymo’s Foundation Model pre-training and post-training
Lead and drive science on best practices around clustering, filtering,: de-duplication, long-tail data mining, memorization, etc.
Tech-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. This includes 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
What they're looking for
- 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 Data-centric AI, 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
- Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)
- Extensive experience working with data and recipes for large scale foundation models