Hiring nowAutonomous navigation and field robotics

Localisation and Mapping Engineer

Also called SLAM Engineer

A Localisation and Mapping Engineer builds the system that tells a robot or vehicle where it is and what surrounds it. Without that, nothing downstream can plan, navigate or operate safely.

What they do

Builds and tunes the stack that estimates position and keeps a map of the surroundings. Fuses data from cameras, lidar, inertial units and wheel or GNSS sources. Runs the stack in simulation first, then takes it into the field and studies where it drifts or fails. Writes the tests that replay recorded sensor data. Works with perception, planning and hardware colleagues on timing, calibration and sensor placement. Decides when to trust a sensor and when to stop trusting it. Fixes what the field shows up, and records why.

What a strong hire delivers

Within the first months, a strong hire gets a working localisation and mapping stack running on real hardware, with a clear baseline for position error. They put in place replay and simulation tests so changes can be judged quickly. They document known failure cases, and show the system recovering when a sensor drops out or degrades. The team gains a shared view of what the stack can and cannot do.

How you can tell they are good

Ask them to walk through a system they took into the field. Good candidates describe real failures, such as drift, bad loop closures or calibration faults, and what they changed. They can explain why they chose a filter or a graph approach. They talk about uncertainty, not only averages. Ask how they would know the estimate was wrong. Vague answers about accuracy with no field evidence are a warning.

Why it is hard to fill

Titles vary, and the same work sits under SLAM, state estimation, perception or autonomy. Many candidates have strong theory or strong software skills but little time on real hardware in messy conditions. Others have only worked on one sensor setup. The people who have shipped and debugged a stack in the field are few, and they are usually already busy.

Where to find them

Look in robotics and autonomy teams working on mobile robots, drones, vehicles and inspection or agricultural machines. Strong candidates come from estimation, controls, computer vision and geomatics backgrounds. Research labs and university robotics groups produce good people, but check for field experience. Engineers from AR and mapping companies can also move across well.

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 Localisation and Mapping Engineer

  1. Tell me about a localisation system you validated in the field. What went wrong first?

    Strong answers name specific failures, such as drift, poor calibration or bad data association, and the fix that followed. They show evidence from real runs. Worry if the story only covers simulation or clean datasets.

  2. How do you decide between a filter-based and a graph-based approach for a new platform?

    Look for trade-offs in compute, latency, sensors, map size and need for global consistency. Good candidates tie the choice to the product. Worry about a favourite method applied to every problem.

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

Job description you can post

We build autonomous systems that operate in real physical environments. We are looking for a Localisation and Mapping Engineer to own how our platform knows where it is and what is around it. The work runs from algorithm design through to field validation on real hardware.

What you will do

  • Design and maintain our localisation and mapping stack
  • Fuse data from cameras, lidar, inertial and other sensors
  • Measure position error and track it across releases
  • Build replay and simulation tests for regression checking
  • Investigate field failures and ship fixes
  • Define how the system detects and recovers from sensor degradation
  • Work with perception, planning and hardware engineers on calibration and timing

What you will bring

  • Shipped a SLAM or state estimation system that ran on real hardware
  • Working knowledge of filtering and graph optimisation methods
  • Strong C++ or comparable systems programming, shown in code or projects
  • Experience debugging calibration, timing and data association problems
  • Experience with ROS or similar frameworks
  • Clear account of how you measured and validated performance in the field

Nice to have

  • Experience with multi-sensor fusion across several platform types
  • Work on uncertainty estimation and consistency testing
  • Experience building simulation or digital twin test environments

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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