We build the software that decides how our autonomous vehicles move through the world. Our systems predict the behavior of pedestrians, cyclists, and other vehicles, then plan trajectories that are safe, comfortable, and legible to the people around them. We work at the intersection of machine learning, large-scale data infrastructure, and real-time vehicle control, collaborating across engineering, analytics, and product teams to deliver safe and intelligent driving capabilities.
Before you apply: This role requires hands-on experience building systems that predict how other agents will move and deciding how a vehicle or robot should act in response — deployed on real hardware, not only in simulation or research. If your machine learning experience is primarily in NLP, recommendations, tabular data, or academic research without deployed systems, this specific role likely isn’t the right fit, though we encourage you to look at our other openings.
We are looking for a creative & driven Machine Learning Engineer to join our autonomous vehicle team. You will be at the center of our efforts to build intelligent systems that can understand, predict, and safely navigate a complex and dynamic world. You will design and train the models that anticipate what other road users will do next, and turn those predictions into driving decisions. This means working with petabytes of real driving data, building evaluation frameworks that actually correlate with on-road safety, and shipping models that run under hard latency budgets on embedded hardware.
In this production engineering role, you will spend meaningful time on failure analysis, long-tail scenarios, and the gap between offline metrics and on-road behavior. If you are passionate about applying cutting-edge ML to solve high-stakes robotics challenges, we want to hear from you.