> Markdown version of [/jobs/ext/3725666-senior-computer-vision-engineer-localization](https://www.wearedevelopers.com/jobs/ext/3725666-senior-computer-vision-engineer-localization). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Computer Vision Engineer - Localization - **Company:** SE3 Labs - **Location:** München, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Neural Networks, Computer Vision, C++ (Programming Language), Nvidia CUDA, Software Debugging, Linux, Microprocessors, Global Positioning Systems (GPS), Inertial Navigation Systems, Python (Programming Language), Log Analysis, Machine Learning, Regression Testing, State Estimation, Robotic Automation Software, Sensor Fusion, Graphics Processing Unit (GPU), Real Time Systems, Virtual Reality, Information Technology, Low Latency, Production Code, NVIDIA Jetson, GNSS - **Published:** October 14, 2026 - **Apply:** https://startup.jobs/senior-computer-vision-engineer-localization-se3-labs-10445523 ## About the Role * You hold an M.Sc., Ph.D., or equivalent practical background in Robotics, Computer Vision, Electrical Engineering, Computer Science, Aerospace Engineering, or a related technical field. * You bring several years of hands-on experience building perception, SLAM, VIO, localization, sensor-fusion, or state-estimation systems for real-world robotics, AR/VR, autonomous vehicles, drones, or adjacent domains. * You have strong foundations in 3D geometry, linear algebra, probability, estimation theory, optimization, filtering, and real-time robotics systems. * You write production C++ for Linux systems and use Python for analysis, evaluation and tooling. Rust experience is a plus. * You have practical experience with techniques such as EKF, factor graphs, nonlinear least squares, bundle adjustment, visual odometry, inertial navigation, calibration, and multi-sensor fusion. * You have worked with real sensors and understand that perception failures often come from timing, calibration, vibration, lighting, motion blur, data quality, or integration issues rather than from the algorithm alone. * You care about metrics, logs, reproducibility, and systematic validation. You don't just make a demo work once; you build the tools to know when it works, when it fails, and why. * You speak fluent English; German is a plus. Given the nature of SE3's work in the defence sector, candidates must be eligible to work on defence-related projects and, where required, obtain the relevant security clearance., * Experience deploying perception systems on Nvidia Jetson, embedded CPUs/GPUs, writing CUDA kernels, optimizing deep neural networks for edge deployment. * Experience with LWIR thermal cameras (for navigation), rolling shutter effects, visual-inertial calibration, multi-camera rigs, fisheye/wide-angle lenses or monocular depth. * Experience with GNSS-denied navigation in UAV context, terrain-relative navigation, map-based localization and re-localization. * Experience building evaluation datasets, replay systems, perception observability, log tooling, and automated regression pipelines. * Publications or open-source contributions in SLAM, VIO, 3D computer vision, state estimation, or robotics are welcome, but not required. ## Description As Senior Computer Vision Engineer - Localization (VIO / SLAM / Sensor Fusion), you will own core parts of the real-time perception and localization stack for our autonomous systems. You will develop and deploy the algorithms that let our platforms estimate motion, maintain pose, build spatial understanding, and operate reliably in degraded or GPS-denied environments. You will work across visual-inertial odometry, SLAM, sensor fusion, calibration, time synchronization, mapping, and real-time systems. Your work will sit at the center of our autonomy platform: connecting cameras, IMUs, GNSS, onboard compute, control systems, payloads, and Spatial AI models into a coherent understanding of the world. This is a hands-on engineering role. You will design algorithms, write production code, analyze logs, debug sensor issues, validate performance in simulation and flight, and work closely with robotics software, embedded, hardware, and field teams to turn perception research into fieldable capability., * Robustness in difficult conditions: Improve state estimation capabilities in very difficult field conditions during heavy rain, snow, fog, in the night, under strong vibration, motion blur, imperfect calibration and sensor degradation. Compare improved sensor fusion and learned methods using recorded data and field results. * VIO & State Estimation: Build, tune, and deploy robust visual-inertial odometry and state-estimation pipelines for robotics systems operating in dynamic, outdoor, and GPS-challenged environments. Initial focus is on UAVs, but we want to build algorithms that work well for any robotics system. * Sensor Fusion: Fuse and synchronize data from cameras, IMUs, magnetometers, barometers, and other onboard sensors into reliable pose, orientation, uncertainty estimates, and spatial context for downstream autonomy. * SLAM & Re-localization: Build mapping, loop closure, re-localization, and map-based navigation capabilities that let our systems maintain spatial understanding across missions, environments, and degraded sensor conditions. * Calibration & Timing: Own intrinsic, extrinsic, and temporal calibration workflows. Diagnose drift, latency, frame drops, sync issues, rolling-shutter effects, vibration, and sensor degradation. * Real-Time Deployment: Optimize perception pipelines for onboard compute, including Nvidia Jetson-class platforms, low-power edge CPUs/GPUs, and resource-constrained robotic systems. * Validation & Regression: Build replayable log pipelines, evaluation datasets, test metrics, and automated regression tests to measure localization accuracy, robustness, latency, and failure modes on our internal benchmark datasets. * Field Debugging: Analyze real mission logs, reproduce failures, isolate root causes, and improve the system until it works not only in ideal conditions, but in the field. * Autonomy Integration: Define clean interfaces to planning, control, fleet coordination, operator UI, and Spatial AI systems so that perception outputs are usable, reliable, and explainable. * Technical Leadership: Mentor engineers, review architecture and code, raise engineering standards, and help define the long-term perception roadmap for SE3's autonomous systems.