Develop, evaluate, and release learned driving policies for complex navigation and yielding
Work cross-functionally at the intersection of perception and planning, translating multi-modal
Deploy learned models into closed-loop simulation environments, benchmark against strict safety
Advance the transition from rule-based heuristics to scalable, data-driven learned policies.

🎯 Requirements

2–5+ years experience training and releasing ML models in autonomous driving, robotics, or complex
Hands-on experience working across both perception and planning stacks. Proficiency in learned
Familiarity with Vision-Language-Action (VLA) models and World Models is a strong plus.
Experience using foundation models and AI tools for scenario generation, evaluation analysis, and

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