Senior SLAM/Perception Engineer

pbWho we are /b /ppEvolunar is a deep-tech aerospace startup and spin-off of Politecnico di Torino, developing advanced autonomous navigation technologies for UAVs and robotic platforms. Born from the challenge of navigating on the Moon, our technology is now enabling autonomous systems to operate in some of the most demanding GNSS-denied and degraded environments on Earth. /ppbr/ppbAbout the role /b /ppWe're looking for a Senior SLAM Engineer to work on the perception and navigation stack at the core of our autonomous navigation system, enabling UAVs to fly where GNSS is denied or degraded. /ppYou will own core parts of the real-time estimation pipeline, from the computer vision front-end to the state estimation back-end, and you will be responsible all the way from research prototypes to optimized production code running at high rate on a resource-constrained flight computer. /ppYou'll work at the intersection of computer vision, sensor fusion, and state estimation, alongside a small team of engineers with expertise in robotics, estimation theory, and real-time systems. /p pbWhat you'll do /b /pulliDesign, prototype, and validate SLAM, visual-inertial odometry, and state estimation algorithms. /liliOwn the front-end: feature detection and tracking, data association, outlier rejection, multi-camera and multi-sensor geometry and map matching. /liliOwn the back-end: EKF and/or factor-graph estimation, tightly-coupled sensor fusion, loop closure and relocalization, consistency and observability analysis. /liliSupport integration and flight testing, debug from real flight data, and feed what you learn in the field back into the algorithms. /liliWrite efficient and optimized production C++ code. /liliContribute to architecture decisions, code reviews, and the technical growth of the team. /li /ulpbr/ppbWhat you'll bring /b /ppbRequired /b /pulliMSc or PhD in Computer Science, Robotics, Engineering, or a related field, or a BSc with equivalent hands-on experience. /lili3+ years developing perception and state estimation algorithms for real-time robotic systems. /liliStrong grounding in probabilistic estimation: EKF and/or factor graphs. /liliDeep understanding of visual-inertial odometry and multi-sensor fusion. /liliA track record of designing, implementing, and debugging core elements of complex SLAM systems. /liliSolid computer vision and image processing fundamentals: multi-view geometry, camera models, calibration. /liliReal experience writing optimized, maintainable, production code in C++. /liliExperience in MATLAB and/or Python for prototyping, analysis, and tooling. /liliAbility to diagnose problems in a real system from flight collected data. /li /ulpbNice to have /b /pulliExperience with learning-based perception: learned features and matching, monocular depth, place recognition. /liliKnowledge of multi-sensor extrinsic and temporal calibration. /liliExperience in safety-critical or aerospace development environments. /li /ulpbr/ppbWhat we offer /b /pulliOwnership of a core technical area, with real influence over the architecture and direction of the navigation stack. /liliWork at the forefront of autonomous robotics, pushing the state of the art on problems that are still open. /liliA fast development cycle, where your work is promptly validated on real hardware in real conditions, not only in simulation. /liliAn early role on a fast-growing, technically ambitious, and fast-paced team, with a direct path to future leadership. /liliCompetitive salary of € 38k – 48k. /liliFlexible hours, hybrid working. /li /ulpbr/p