waymo · Mountain View, California, USA
Waymo 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, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo 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. Role overview: Autonomy MLE role focused on bridging perception and planning to develop and release robust learned driving policies. The primary objective of this role is to train, evaluate, and transition production-ready decision-making models into real-world autonomous navigation systems. In this hybrid role, you will report to the Technical Lead Manager. You will: Develop, evaluate, and release learned driving policies for complex navigation and yielding scenarios. Work cross-functionally at the intersection of perception and planning, translating multi-modal perception outputs into robust behavioral actions. Deploy learned models into closed-loop simulation environments, benchmark against strict safety metrics, and drive the transition of these models into production releases. Advance the transition from rule-based heuristics to scalable, data-driven learned policies. You have: 2–5+ years experience training and releasing ML models in autonomous driving, robotics, or complex spatial AI. Hands-on experience working across both perception and planning stacks. Proficiency in learned driving policies (RL / imitation learning), PyTorch / JAX, closed-loop simulator evaluation, and a track record of releasing models to production. Familiarity with Vision-Language-Action (VLA) mode…
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