Robotics Autonomy Engineer, Planning & Control (Federal)

What you'll do

• Develop motion and navigation planning, path and trajectory generation, and control algorithms for diverse robotic systems.
• Integrate planning and control with perception and other autonomy layers; validate performance through testing, simulation, and robot deployment.
• Analyze telemetry and field issues, debug failures, and improve algorithm robustness.

What they ask for

• PhD in Robotics, Computer Science, Electrical Engineering, or a related field with 2+ years of industry or applied research experience; or MS in a related field with 4+ years of relevant experience; or BS in a related field with 8+ years of relevant experience.
• Strong understanding of motion planning, trajectory generation, and control systems; algorithm development experience with at least one listed robotic system.
• Solid programming skills in C++ and Python on Linux-based systems.
• Familiarity with motion-planning libraries, robotics middleware such as ROS/ROS 2, and robot sensors.

Nice to have

• Exposure to real-world deployment of autonomous systems; background in optimization, control, or numerical methods for trajectory planning.
• Familiarity with learning-based or hybrid planning, open-source planning or control frameworks, or safety-critical autonomy and industrial robotics.

Pay

USD 100,000–200,000 per-year-salary (base salary)

Tools

OMPL, MoveIt, Nav2 stack, C++, Python, Linux, ROS/ROS 2

AI focus

Develop autonomy planning and control for field-ready robots; the posting also describes Field Foundational Models for perception, planning, localization, and manipulation.