Machine Learning Engineer / Applied Scientist, Prediction & Planning

The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver's behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks.

These models enable the autonomous vehicle to navigate complex environments safely and efficiently.

- Design, implement, and evaluate state-of-the-art generative models for autonomous vehicle planning and prediction

- Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo's business

- Translate open-ended, real-world driving challenges into well-defined machine learning problems, applying cutting-edge techniques, including foundation models and reinforcement learning

- Write high-quality, scalable, and thoroughly tested code to bring cutting-edge research into production

- Partner with world-class researchers, engineers, and product managers to deliver safe and smooth planning behaviors, and publish findings at top-tier academic venues

- PhD in Computer Science, Machine Learning, Robotics, a related technical field, or equivalent practical experience

- A proven track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)

- Demonstrated impact on the broader ML community through influential research, widely adopted open-source projects, or significant industry contributions

- Hands-on expertise with modern deep learning frameworks, for example JAX or PyTorch

- Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities

- Specialized research experience in deep learning, reinforcement learning, causal reasoning, or foundation models

- Prior industry experience (e.g. internships) in applied ML research or software development

- Domain expertise in solving motion planning, prediction, or related robotics problems

- Hands-on experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments