Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML

Highlights

• Build learned driving policies bridging perception and planning for autonomy.
• Release robust policies for complex navigation and yielding scenarios at scale.
• Advance shift from rule-based heuristics to scalable data-driven driving policies.

What they offer

• Annual bonus program
• Equity incentive plan
• Company benefits program

Ideal candidate

An autonomy-minded ML engineer with 2-5+ years shipping real-world models who thrives at the perception-planning intersection and cares about safe, scalable learned driving behavior.

Requirements

• 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 track record of releasing models to production
• 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 rapid experimentation