Machine Learning Engineering TL, Behavior Planning

Architect and deploy large-scale onboard planning models trained with Imitation Learning and Reinforcement Learning to enable safe, efficient autonomous driving.
Design and build a next-generation simulation engine with offboard foundation models to create realistic world models and test edge cases.
Develop offboard critic models for scalable evaluation of driving behavior across comfort, progress, and safety metrics.
Bridge research and production by pushing state-of-the-art techniques into real-world vehicle deployments that meet stringent safety standards.
Mentor and lead junior engineers, helping define the long-term ML-based planning roadmap and the required onboard and offboard ecosystem.
Work in a fast-paced, collaborative environment with a focus on safety, reliability, and impactful, scalable machine learning systems.