Tech Stack

Description

You will design and ship deterministic, safety-critical planning systems that ensure autonomous vehicles behave safely when autonomy degrades. You'll work on fallback and minimal-risk maneuvers, using large-scale simulation and real-world data to evaluate planner behavior.

Requirements

• 5+ years of experience in motion planning for autonomous vehicles or robotics
• Strong foundation in robotic motion planning algorithms and trajectory generation (optimization-, search-, or rule-based)
• Experience building deterministic, safety-critical planning systems
• Data-driven mindset for large-scale evaluation, debugging, and tuning of planning behavior
• Proficiency in C++ and experience working in real-time systems

Responsibilities

• Design and implement classical or ML motion planners for fallback and minimal-risk maneuvers
• Build planners that operate reliably under degraded perception, partial observability, and system faults
• Define and execute safe, deterministic vehicle motions such as controlled slow-downs, pull-overs, and safe stops
• Use large-scale simulation and real-world data to evaluate planner behavior and guide parameter tuning
• Collaborate closely with behavior prediction, perception, controls, safety, and remote assistance teams