Tech Stack

Description

You will own the local mobility and safety stack for our fleet, bridging AI-driven perception with physical hardware execution. You'll translate AI-generated costmaps into safe, dynamically feasible motion for our humanoid platform on unpredictable terrain.

Requirements

• Ph.D. in Robotics, Mechanical Engineering, CS, or related field, or M.S. with 4+ years industry experience
• Deep hands-on experience developing local planners and trajectory optimization for mobile robots in unstructured environments
• Strong understanding of kinematics, vehicle dynamics, and CoM constraints for top-heavy mobile robots
• Expertise in modern C++ (C++17/20) with focus on real-time performance and low-latency execution
• Proven track record of deploying autonomous navigation stacks on real robots in the wild; requires 5 days/week in-office

Responsibilities

• Architect and implement advanced local planners (MPC, MPPI, contouring control) for dynamic motion planning on uneven terrain
• Build high-performance C++ pipelines to ingest AI neural network outputs into deterministic mathematical constraints
• Ensure local planners dynamically adjust to real-time changes in the robot's Center of Mass for stability on slopes
• Implement deterministic C++ safety layer and fallback behaviors to override AI inputs that violate physical constraints
• Architect interfaces to pass base trajectories and constraints to Whole-Body Control (WBC) architecture