We are looking to recruit an exceptional Robot Autonomy Engineer to build the decision-making stack that turns a goal into coordinated, reliable robot behavior in real industrial applications — what the robot should do next, in what order, and how a fleet of them shares one facility without getting in each other’s way.
In this role you will:
- Own the autonomy stack above the controller — task planning, behavior planning, path planning and trajectory planning — from the moment work arrives to the trajectories handed off to motion control.
- Design the behavior architectures that structure long-horizon manipulation and navigation tasks, and that degrade into retry, recovery and operator handoff rather than into a stall.
- Bring principled task planning to industrial workflows: goal and precedence reasoning, task allocation, and planning under uncertainty.
Plan and coordinate motion for multiple robots sharing an industrial facility — separation, reservation, deconfliction and deadlock-free repositioning — so that adding a robot adds throughput.
- Integrate LLM and VLM reasoning into planning for task decomposition, subtask grounding and language-conditioned goals, together with the verification and fallbacks that make a model’s output safe to execute on real hardware.
- Define the contract between learned policies and classical planning: what the model may decide, what the planner must guarantee, and how the two hand off mid-task.
- Interface with perception, intelligence, controls, simulation and platform software in designing functional architectures that hold up under real-world operation.
- Hold the whole stack to measurable field performance — cycle time, success rate, intervention rate — through simulation, replay of recorded robot logs, and testing on real robots.
