Robotics Autonomy Engineer-Planning and Control

About the Job

• Field AI is building the future of autonomy—from rugged terrain to real-world deployment. We’re on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments. 
• As our Robotics Autonomy Engineer – Planning and Control, you’ll design, implement, and deploy advanced motion planning and control algorithms that enable our robots to move with precision, robustness, and efficiency across diverse environments.
• You’ll work on navigation, trajectory generation, and motion control for robotic platforms ranging from wheeled and legged systems to complex humanoid architectures.
• If enabling robots to navigate challenging, dynamic environments excites you, and you want to work where your code hits the ground (literally) — this is your role. This is Field AI.

What You'll Get To Do

• 1. Develop Robust Motion Planning Algorithms
• Design, develop, and refine motion and navigation planning algorithms for challenging real-world scenarios such as narrow passages, dynamic obstacles, and complex environments.
• Design optimization-driven approaches for path and trajectory generation that ensure smooth, reliable, and efficient robot navigation across modalities.
• Ensure scalability, reusability, and adaptability of planning approaches across diverse deployment contexts.


• 2. Advance Control and Planning Integration
• Develop and tune control algorithms that ensure precise trajectory tracking and stable operation across different robotic systems.
• Collaborate across autonomy layers to ensure seamless coordination between perception, planning, and control for robust real-world performance.


• 3. Validate and Test Across the Stack
• Build and maintain testing pipelines from unit-level validation to full robot deployment.
• Utilize simulation and testing environments for algorithm evaluation, benchmarking, and regression validation.
• Analyze real-world telemetry to diagnose issues, identify improvements, and enhance algorithm robustness.


• 4. Diagnose and Improve Field Performance
• Investigate and resolve issues arising from field deployments through structured data analysis and debugging.
• Deliver targeted improvements that address specific challenges while maintaining general-case reliability and performance.

What You Have

• Master’s degree or higher in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field (PhD a plus).
• Strong understanding of motion planning, trajectory generation, and control systems.
• Experience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid).
• Solid programming skills in C++ and Python on Linux-based systems.
• Familiarity with robotics middleware such as ROS/ROS 2.
• Experience with robot sensors including LiDARs, stereo/depth cameras, IMUs, GPS, wheel encoders

The Extras That Set You Apart

• 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 approaches.
• Contributions to open-source planning or control frameworks.
• Familiarity with safety-critical autonomy and industrial robotics use cases.