Senior/Staff Robotics Autonomy Engineer-Planning and Control (Federal)

Field AI is transforming how robots interact with the real world by building risk-aware and reliable AI systems. The Robotics Autonomy Engineer - Planning and Control will design and implement advanced motion planning and control algorithms for robots, ensuring they navigate complex environments with precision and efficiency.

Responsibilities:

• 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
• 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
• 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
• 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

Requirements:

• PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field with 2+ years of industry or applied research experience or MS degree in a related field with 4+ years of relevant experience, or BS degree in a related field with 8+ years of relevant experience
• Strong understanding of motion planning, trajectory generation, and control systems
• Experience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid)
• Familiarity with motion planning libraries like OMPL, MoveIt, Nav2 stack etc
• 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
• 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