Waymo's Optimization team maintains and improves a high impact system that is a critical part of Waymo's Planner. You will work at the intersection of robotics and modern ML, collaborating across our teams, to build solutions that can handle situations from everyday driving to ones that happen once in a million miles.

In this hybrid role, you will report to a Staff Engineering Manager within Behavior.

You will:

• Work with a creative team of people who ensure that the behavior of our cars is safe, smooth, and predictable to other road users, which includes gracefully handling many complex situations involving social aspects (merging, negotiating narrow roads), while dealing with noisy, uncertain, and incomplete information.
• Frame the open-ended real-world problems into well-defined ML problems; apply deep learning, reinforcement learning, imitation learning to these problems; scale them to Google-sized data pipelines; and refine them to run in real-time on the cars.

You have:

• BS in Computer Science, ML, Robotics, similar technical field of study, or equivalent practical experience
• 5+ years of experience solving problems using Machine Learning with Tensorflow or equivalent tools and integrating ML in a production system
• Experience evaluating ML-based systems

We prefer:

• Experience applying machine learning to solve motion planning or related robotics problems
• PhD in Computer Science, ML, Robotics
• Experience with Deep Neural Networks or Regression Models

#LI-Hybrid