Senior 3D Mapping Engineer (Large-Scale 3D/HD Mapping) - First Key Hire
Circa £80k+, London based
An opportunity to take ownership of the mapping capability inside an advanced autonomy start up building real-world robotic systems.
This role sits at the heart of the autonomy stack. The focus is the creation of high-accuracy, reusable 3D / HD maps that support reliable deployment across complex environments. As the first dedicated mapping hire, responsibility sits with you to evolve the mapping architecture, deepen the mathematical foundations behind it, and ensure the maps produced are stable, scalable and production ready.
Working closely with perception, localisation and navigation engineers, the goal is to turn raw multi-sensor data into precise, reusable map products that can be versioned, updated and deployed across fleets. Over time, this role will naturally grow into leading and building the mapping team.
What you'll be doing
- Designing and evolving scalable LiDAR and vision-based mapping pipelines.
- Creating high-fidelity 3D / HD maps suitable for repeated autonomous deployments.
- Building robust spatial representations including occupancy grids, vector maps, semantic layers and environment models.
- Applying optimisation techniques such as factor graphs, bundle adjustment and pose graph optimisation to maintain global consistency.
- Leading multi-sensor fusion across LiDAR, cameras, radar, GNSS/INS and odometry.
- Developing large-scale capabilities including multi-session mapping, map versioning, delta updates and fleet workflows.
- Ensuring tight coupling between mapping, SLAM and localisation to guarantee drift-free operation.
- Defining accuracy, consistency and validation frameworks for deployed maps.
Experience required
- MSc or PhD in Robotics, Computer Vision, Computer Science, Mathematics or a related field.
- 4-5+ years building mapping systems for robotics or autonomous platforms operating in real-world environments.
- Proven experience creating high-accuracy 3D / HD maps designed for reuse across deployments, not just one-off mapping or research prototypes.
- Strong understanding of the mathematical foundations behind mapping, including pose graphs, factor graphs, bundle adjustment and probabilistic estimation.
- Deep experience working with LiDAR and large-scale point cloud processing (PCL, Open3D or similar).
- Experience combining multiple sensor sources such as LiDAR, cameras, GNSS/INS and odometry to generate globally consistent maps.
- Strong C++ development with experience working in ROS2-based autonomy stacks.
- Solid grounding in geometry, coordinate frames, kinematics and transformation systems.
Why join
You'll own a mission-critical capability inside a company deploying autonomy in the real world, shaping the mapping stack, influencing the wider autonomy architecture and building the team that will take it forward. An opportunity to define how mapping works in a real-world autonomy platform from the ground up
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