Machine Learning Engineering TL, Behavior Planning

Lead architecture and deployment of onboard planning models trained with imitation learning and reinforcement learning to enable safe, human-like, high-performance autonomous navigation.
Design and build a next-generation simulation engine with offboard foundation models to create realistic world models for exhaustive edge-case testing.
Develop offboard critic models to evaluate driving behavior at scale, capturing nuances in comfort, progress, and safety beyond traditional heuristics.
Bridge research and production by pushing state-of-the-art while deploying models to public-road vehicles meeting strict safety standards.
Mentor and lead junior engineers, shaping the long-term roadmap for ML-based planning across onboard and offboard ecosystems.
Collaborate across teams, leverage distributed training on large datasets, and contribute to safety-first engineering culture.