About the job
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.
Responsibilities
Drive the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet.
Lead efforts to generalize complex depot operations using advanced robotics.
Focus on complex depot operations, such as exterior cleaning, sensor calibration, and maintenance checks.
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.
Qualifications
Minimum
At least 10 years of experience applying machine learning techniques to large-scale industrial problems.
Proven experience in training and evaluating large machine learning models.
Expertise in reinforcement learning and its applications to real-world problems.
Preferred
PhD in Machine Learning, Robotics, or a related technical field.
Experience in robotics or embodied AI is a plus.
Background in collaborating with internal and external research partners on applying ML to large-scale industry scale problems.