Machine Learning Engineer, Depot Automation

This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations—such as exterior cleaning, sensor calibration, and maintenance checks—using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.

This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors.

You will:

• Drive the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet
• Contribute to accomplishing complex depot operations using advanced robotics
• Focus on complex depot operations, such as charging, interior cleaning, vehicle inspection, and routine vehicle maintenance tasks
• Leverage foundation models, reinforcement learning, and simulation
• Integrate ML models in production at scale
• Interface closely with operations teams to translate real-world needs into robust, working solutions

You have:

• 3+ years of experience in training and evaluating large machine learning models
• 3+ years of experience with robotics, preferably industrial robotics 
• Expertise in reinforcement learning and its applications to real-world problems

We prefer:

• A PhD in Machine Learning, Robotics, or a related technical field or equivalent experience 
• Experience with applying machine learning techniques to large-scale industrial problems is a plus
• Background in collaborating with internal and external research partners on applying ML to large-scale industry scale problems