Global Mapping Engineer – SLAM

Responsibilities

• Design and deploy large-scale georeferenced mapping systems for autonomous heavy machinery operating in continuously evolving construction environments.
• Develop global dynamic mapping pipelines that maintain accurate, up-to-date site representations across evolving terrain, active construction operations, and machine activity.
• Define performance metrics, validation methodologies, and benchmarking frameworks for map quality, localization accuracy, robustness, and runtime performance.
• Develop scalable multi-sensor fusion and SLAM algorithms that enable robust mapping, localization, state estimation, and calibration in challenging outdoor environments with degraded or intermittent GNSS.
• Collaborate closely with multidisciplinary experts to improve the reliability, scalability, and field performance of the overall system.
• Ensure production-quality implementation, documentation, and timely execution in a fast-paced, deployment-driven environment.

• Master’s or PhD in Computer Science, Robotics, Mechanical Engineering, Electrical Engineering, Geomatics, or a related field.
• 3+ years of experience developing mapping, SLAM, localization, or state estimation systems for real-world robotic platforms.
• Strong understanding of coordinate frames, calibration, sensor synchronization, uncertainty modeling, and real-time robotics systems.
• Experience building multi-sensor mapping pipelines using GNSS, LiDAR, cameras, IMUs, and other sensor data.
• Strong experience with mapping and SLAM algorithms such as LiDAR-inertial odometry, pose graph optimization, loop closure, scan matching, map alignment, and georeferencing.
• Experience writing production-quality C++ and/or Python code in a Linux development environment.
• Experience evaluating mapping and localization performance using clear metrics, datasets, field-testing procedures, and benchmarking frameworks.