Group Lead Robotics Perception, Mapping & Navigation (human)

Your mission & challenges Technical roadmap: You own the technical roadmap for perception, mapping and navigation, from research prototypes to production on real robots. Build & lead the team: You hire a team of perception, SLAM and navigation engineers, mentor them and support each person’s growth. Multi-sensor perception: You drive perception across multiple sensors (RGB-D, stereo, LiDAR, IMU, wheel odometry), including calibration, time synchronisation and sensor fusion. SLAM, localisation & map management: You lead the development of SLAM, localisation and map management (2D/3D, semantic and long-term maps, multi-session mapping, map updates in changing environments). 3D scene understanding: You own object detection, segmentation, pose estimation and scene representations (occupancy, voxel, mesh, neural fields) that feed manipulation and planning. Navigation: You drive global and local path planning, obstacle avoidance, navigation around dynamic and human obstacles, and whole-body motion in cluttered spaces. Real-time performance: Together with the Edge AI and hardware teams, you ensure real-time requirements are met on embedded compute. Functional safety: You work with the safety team to meet the requirements for autonomous motion (e.g. ISO 13482, ISO 3691-4, ISO 10218). Simulation, data pipelines & evaluation: You build datasets, ground truth, KPIs and regression testing in simulation and on hardware. Hands-on on hard problems: You get stuck in yourself when localisation failures, drift, degenerate environments or field edge cases come up. What we can look forward to Education: Master’s or PhD in robotics, computer science, electrical engineering or a related field. Experience: 7+ years in robotics perception, SLAM or navigation, including 2+ years of technical leadership and deployments on real robots in production or field settings. State estimation & SLAM: Deep knowledge of state estimation, sensor fusion and SLAM (e.g. factor graphs, visual-inertial odometry, LiDAR SLAM). 3D computer vision: Strong background in 3D computer vision and learning-based perception. Motion planning & navigation: Solid experience with motion planning and navigation stacks (e.g. ROS 2, Nav2, MoveIt). Simulation: Experience with simulation tools (e.g. Isaac Sim, Gazebo, MuJoCo) and sim-to-real transfer. Tech stack: Strong C++ and Python, Linux, PyTorch, and libraries such as GTSAM, Ceres, Open3D, PCL or OpenCV. Leadership & communication: Strong leadership and communication skills, with professional English in speaking and writing. German at B2 to C1 is a strong plus.