Field AI
Robotics
Senior/StaffRoboticsAutonomyEngineerPlanningandControl(Federal)
“Senior/Staff Robotics Autonomy Engineer-Planning and Control (Federal) at Field AI. Skills: Robotics Autonomy, Planning, Control, Motion Planning, Trajectory Generation, C++, Python. Design, develop, and refine motion and navigation planning algorithms for challenging real-world scenarios. Design optimization-driven approaches for path and trajectory generation”
What You'll Achieve.
unlocking the full potential of embodied intelligence; delivering real-world results; rapidly improving models through real-field applications; enable our robots to move with precision, robustness, and efficiency across diverse environments; ensure smooth, reliable, and efficient robot navigation across modalities; ensure seamless coordination between perception, planning, and control for robust real-world performance; enhance algorithm robustness; address specific challenges while maintaining general-case reliability and performance; set a new standard in perception, planning, localization, and manipulation; achieve our ambitious goals
Industry & Context.
address the most complex challenges in robotics; diagnose issues; identify improvements; enhance algorithm robustness; investigate and resolve issues; deliver targeted improvements
Federal
What They're Looking For.
Must Have
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, 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
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 approaches, Contributions to open-source planning or control frameworks, Familiarity with safety-critical autonomy and industrial robotics use cases
What You'll Do.
and refine motion and navigation planning algorithms for challenging real-world scenarios
Design optimization-driven approaches for path and trajectory generation
and adaptability of planning approaches
Develop and tune control algorithms
Collaborate across autonomy layers to ensure seamless coordination between perception
Build and maintain testing pipelines
Utilize simulation and testing environments for algorithm evaluation
and regression validation
Analyze real-world telemetry to diagnose issues
identify improvements
and enhance algorithm robustness
Investigate and resolve issues arising from field deployments
Deliver targeted improvements
How You'll Work.
Team & Collaboration
Collaborate across autonomy layers to ensure seamless coordination between perception, planning, and control for robust real-world performance; work with a world-class team; close-knit team
Communication Scope
communicators
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