München, Bayern, Deutschland
Own the spatial state-estimation layer of our autonomy platform. Build the perception systems that let drones understand where they are, what they see, and how to operate when GPS, lighting, timing, and the real world get difficult.
SE3 Labs builds spatial intelligence and autonomy software for unmanned systems. We combine 3D computer vision, state estimation and AI to help autonomous platforms perceive their surroundings, know where they are and operate when GPS and other sensors become unreliable. Defence is a core application of our work today.
We are growing to a team of 100+ people. Join at a stage where you can shape our localization technology, help build the team and grow your responsibilities as the company expands.
Our founding team’s research has received more than 90,000 citations. You will work closely with technical founders and engineers with deep experience in computer vision and autonomous systems, turning that research depth into systems that work in the field.
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.
You take ownership of a problem from diagnosis through implementation and validation. You work quickly, investigate root causes and use measured results to decide what to improve next.
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.
Real Ownership: Participate in SE3’s growth through our employee participation programme
Work Environment to Excel at: Find a high-quality and modern toolset, flat hierarchy and a skilled, driven team which will push the limits together with you
AI-boosted workplace: We empower every employee with best-in-class AI tools and agents, giving you unlimited access to the latest advancements and a true productivity edge
31 Paid Days Off: 30 vacation days plus your birthday off
Well-being Access: Free membership to gyms, yoga, and wellness through EGYM Wellpass
Team Offsites: We go on 2 company retreats per year, our last ones were in Italy and Greece
Mentorship: Work closely with experienced engineers and get paired with a professional mentor to support your growth
Intro Call (30 min): Let’s get to know each other
Technical Conversation (45 Mins): High level discussion about your technical experience and what we are working on
Coding / Algorithm Interview: We work through a practical perception, estimation, or robotics software problem together
Technical Interview (90 mins): We dive into your experience with perception, state estimation, SLAM/VIO, robotics, and real-world debugging
Team Dinner / Lunch: Meet the team and see whether it is a good fit on both sides
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