Senior Radar Navigation Engineer (All Genders)
Skdse · 🌍 Munich, Bavaria
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About the role
At Stark, we forge the future of European and national security through cutting-edge, AI-driven technology and unmatched engineering precision. As a premier defence technology company, our mission is clear: to equip NATO Allies and their partners with next-generation autonomous defence platforms and advanced AI-driven software built to perform in the world’s most demanding environments. We believe that true security stems from relentless innovation. By combining elite engineering talent with agile technology and an AI-native operational culture, Stark turns complex defence challenges into field-tested, multi-domain solutions. Why Join Us? • The software and systems you work on directly protect personnel and defend European and national sovereignty. • You will work alongside industry-leading minds on autonomous systems, advanced propulsion, and secure cyber platforms. • We foster a fast-paced, collaborative environment where bold ideas are supported by serious R&D backing. About the Team Our Perception and AI team is responsible for how STARK's unmanned systems perceive their surroundings and know where they are. We are a multidisciplinary group of software and navigation engineers developing perception and navigation algorithms for resource-constrained platforms. As a member of this team, you will collaborate closely with sensor, autonomy and test engineers in a fast-paced, hands-on environment. Together, we make sure our systems navigate and operate reliably in contested environments, even when GNSS is not available. Your Mission As a Senior Radar Navigation Engineer at STARK, you will lead the development of radar-based navigation and mapping: estimating how our systems move and what surrounds them, without relying on GNSS. Your ultimate goal is to deliver motion estimates and 3D maps that our autonomy stack can depend on in the most demanding conditions. Responsibilities - Develop radar odometry and radar-inertial state estimation for position, velocity and orientation in GNSS-denied environments. - Build real-time 3D mapping of the surroundings from radar detections and extract the information our autonomy needs for obstacle avoidance. - Apply SLAM, factor-graph and probabilistic estimation methods within the constraints of embedded, real-time systems. - Define the measurement interface with our radar signal processing engineers and integrate your work with autonomy, embedded software and test teams. - Take algorithms from research prototypes to production C++, and analyse field data to characterise performance and failure modes. - Constantly challenge requirements and take ownership of radar-based navigation as a capability at STARK. What We Are Looking For - You have taken state estimation, localisation or navigation algorithms into production on real-world robotic, automotive or aerospace systems. - Deep understanding of state estimation — SLAM, Kalman filtering, Bayesian estimation, factor graphs — and of 3D geometry, coordinate frames and kinematics. - Strong C++ for real-time systems; Python or MATLAB for prototyping and analysis. - Master's degree or PhD in Robotics, Aerospace Engineering, Electrical Engineering, Computer Science or a comparable field. - Fluent English; German is a plus. - Citizenship of a NATO member state. Nice to Have - Radar odometry or radar-based mapping; lidar or visual odometry also counts - GTSAM, Ceres or similar optimisation libraries - Deployment on resource-constrained embedded compute - Alternative navigation methods and navigation sensor calibration - ROS2 and experience with field testing Relevant Backgrounds Deep expertise in state estimation matters more to us than meeting every single requirement. You might come from robotics research on radar or lidar SLAM, autom