Robotics Autonomy Engineer, Planning & Control (Federal)
Field AI · Irvine, CA
Roboticsonsite$100k–$200k
At a glance
Highlights
- Design robust motion planning for narrow passages and dynamic obstacles.
- Enable wheeled, legged, and humanoid robots to move with precision outdoors.
- Validate autonomy from simulation through full real-world field deployment.
Ideal candidate
A robotics PhD or experienced engineer passionate about real-world autonomy who thrives diagnosing field failures and building robust planning and control that works beyond simulation.
Requirements
- PhD in Robotics, Computer Science, Electrical Engineering or related field with 2+ years experience or MS with 4+ years or BS with 8+ years
- Strong understanding of motion planning, trajectory generation, and control systems
- Experience developing algorithms for wheeled, legged, wheeled-legged or humanoid robotic systems
- Familiarity with motion planning libraries like OMPL, MoveIt, Nav2 stack
- 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
Lab profile
About Field AI
Builds risk-aware embodied AI for autonomous robots in construction, mining, security, and manufacturing.
What they build
- Field-ready embodied AI autonomy stack
- Autonomous robots for harsh environments
- Reality capture and construction monitoring
Known for
- Risk-aware, reliable field-ready AI systems
- Real robots, sensors, and field deployments
- Global operations in harsh environments
- Pragmatic approach beyond off-the-shelf methods
Key facts
- Based in Irvine, California
- R&D team in Boston, Massachusetts
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