Robotics Autonomy Engineer – Planning & Control Hybrid

Field AI

Irvine (CA)

On-site

USD 100,000 - 200,000

Full time

14 days+

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Job summary

Field AI is building autonomous robotics for real-world deployment. As the Robotics Autonomy Engineer – Planning, you will design, implement, and deploy motion planning and control algorithms that enable precise, robust navigation across diverse platforms.

You’ll tackle navigation, trajectory generation, and control for wheeled, legged, or humanoid robots, collaborating with perception and control teams to ensure reliable field performance.

Qualifications

  • Master’s degree or higher in Robotics, Computer Science, Mechanical or Electrical Engineering or related field.
  • Strong understanding of motion planning, trajectory generation, and control systems.
  • Experience developing algorithms for wheeled, legged, or humanoid robotic systems.
  • Familiarity with motion planning libraries like OMPL, MoveIt, Nav2.
  • Solid programming skills in C++ and Python on Linux.
  • Familiarity with ROS/ROS 2 and robotics sensors (LiDAR, cameras, IMUs).

Responsibilities

  • Develop and implement robust motion planning and navigation algorithms for real-world robotics deployments.
  • Tight integration of planning with control for precise trajectory tracking.
  • Validate algorithms through simulation, testing, and field experiments.
  • Collaborate across perception, planning, and control to improve autonomy in dynamic environments.

Skills

Motion planning
Trajectory generation
Control systems
C++
Python
ROS/ROS 2
LiDAR
MoveIt

Education

Master's degree or higher in Robotics, Computer Science, or related field

Tools

OMPL
Nav2 stack

Job description

Field AI is building autonomous robotics for real-world deployment. As the Robotics Autonomy Engineer – Planning, you will design, implement, and deploy motion planning and control algorithms that enable precise, robust navigation across diverse platforms.

You’ll tackle navigation, trajectory generation, and control for wheeled, legged, or humanoid robots, collaborating with perception and control teams to ensure reliable field performance.

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