gravisrobotics - Global Mapping & SLAM Engineer

• 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. • Experience designing large-scale dynamic mapping systems for unstructured or continuously changing environments. • Experience with global mapping, lifelong mapping, multi-session mapping, semantic mapping, or dynamic scene understanding. • Experience with factor-graph optimization frameworks, mapping backends, geospatial data formats, or large-scale map infrastructure. • Experience deploying perception, mapping, or autonomy systems on real-world robots, construction machines, mining vehicles, agricultural machines, autonomous vehicles, or other heavy equipment. • Ability to reason about system-level tradeoffs between accuracy, robustness, latency, scalability, and maintainability. • Strong communication skills and ability to collaborate across robotics, software, hardware, operations, and product teams. • Ability to prioritize effectively and deliver reliable solutions in a fast-paced, deployment-driven environment.