Hiring nowAutonomous navigation and field robotics

Motion Planning Engineer

Also called Autonomy Planning Engineer

A motion planning engineer designs the software that decides how a robot or vehicle moves, so it reaches its goal without breaking physical limits or safety rules. It is what turns perception into safe, useful action.

What they do

The work starts with a goal and a set of limits: speed, acceleration, turning, clearances and safety rules. The engineer builds planners that produce feasible trajectories within those limits and avoid obstacles as the scene changes. Much of the day goes on tuning cost functions, handling edge cases and reading logs from failed runs. They write scenarios in simulation, run them at volume and trace each constraint violation to its cause. They work closely with perception, localisation and controls colleagues, and agree what the planner can assume about uncertain inputs. They also decide what the robot does when it gets stuck.

What a strong hire delivers

In the first months, a strong hire gets the current planner understood, measured and reliably reproducible in simulation. They set up scenario validation that shows where constraints are broken and where tasks fail. They fix the most costly failure patterns and improve recovery behaviour. They leave the team with clear evidence of how the planner performs, and a shared view of what to improve next.

How you can tell they are good

Ask them to walk through a planner they built and where it failed. A strong candidate explains the constraints, the cost trade-offs and how they proved a fix worked. Ask how they handled noisy perception or localisation drift. Listen for evidence from simulation and real runs, and for clear thinking about recovery. Be wary of people who only describe algorithms and never mention validation.

Why it is hard to fill

Titles are inconsistent. The same work appears as planning, autonomy, controls or robotics software, and many candidates have only part of it. Some know optimisation but have never shipped on hardware. Others have shipped but cannot show validation evidence. People with both are few, and they tend to be settled in teams that value them. Backgrounds are mixed, so we screen on demonstrated work, not job titles.

Where to find them

Most come from robotics, autonomy, estimation or control engineering. Look at autonomous vehicle teams, mobile robot and warehouse automation companies, drone and marine autonomy groups, and field robotics firms in agriculture, mining or inspection. Research labs and university robotics groups also produce strong candidates, especially those who have moved their work onto real machines. Controls engineers from aerospace are a useful, often overlooked source.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Motion Planning Engineer

  1. Describe a planner you built. What constraints did it have to respect, and how did you check it did?

    Names specific dynamic and safety limits, and explains how they were encoded and tested. Mentions simulation and real runs. Worry if they describe the algorithm only, or cannot say how violations were measured.

  2. A robot plans well in simulation but hesitates and stops on real hardware. How do you investigate?

    Compares logs between simulation and hardware, and checks localisation noise, latency and model mismatch. Forms hypotheses and tests them one at a time. Worry if they blame the hardware without evidence.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We build autonomous systems that move through real physical environments. We are looking for a motion planning engineer to design planners that generate feasible, safe movements, and to prove with evidence that they work. You will join a small team across perception, localisation and controls.

What you will do

  • Design and improve planners that produce feasible trajectories within dynamic and safety limits
  • Implement trajectory optimisation and collision avoidance for changing environments
  • Build and run scenario validation in simulation and on hardware
  • Analyse logs to find the causes of constraint violations and failed tasks
  • Design recovery behaviour for stuck or degraded situations
  • Agree planning assumptions with perception, localisation and controls colleagues

What you will bring

  • Planners you have built and run on real or simulated systems
  • Demonstrated work in trajectory optimisation and collision avoidance
  • Experience validating planner behaviour with scenarios and clear pass criteria
  • Sound grounding in robotics, control or estimation
  • Experience with ROS and robotics simulators
  • Ability to reason about uncertain inputs from perception

Nice to have

  • Experience with sensor fusion stacks and mapping tools
  • Time spent debugging on field hardware
  • Work on uncertainty quantification in planning

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Robotics and controlAdvancedPerceive, plan and act through physical systems
  • Computer visionAdvancedAnalyse or generate visual information
  • Simulation and digital twinsWorkingBuild useful virtual representations of environments
  • Uncertainty quantificationWorkingEstimate confidence, calibration and model uncertainty

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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