Machine Learning Engineer, Maneuvering Tech

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

• MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience
• 3+ years of industry 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, such as  JAX or PyTorch

Nice to have

• Experience in deep learning, reinforcement learning, and ML systems
• Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems
• ML post-training experience
• 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)