Machine Learning Engineer, Depot Automation

Keystone AI 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, Keystone AI has focused on building the Keystone AI Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Keystone AI Driver powers Keystone AI’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Keystone AI 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. This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Keystone AI'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 Keystone AI'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 The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Keystone AI employees are also eligible to participate in Keystone AI’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $175,000 — $215,000 USD