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 mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Driver Refinement and Validation’s (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans. As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers.
You will:
- Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business
- Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning
- Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production
- Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors
You have:
- MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience
- Hands-on experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments
- Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities
- Expertise with modern deep learning frameworks, for example JAX or PyTorch
We prefer:
- Experience in deep learning, reinforcement learning, and ML systems
- Prior industry experience (e.g. internships) in applied ML or software development
- Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)
- Domain expertise in solving motion planning, prediction, or related robotics problems
