Senior SLAM/Perception Engineer
Pubblicato il 07-09-2026 - Evolunar in Piemonte
Who we are
Evolunar 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.
About the role
We'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.
You 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.
You'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.
What you'll do
- Design, prototype,
and validate SLAM, visual-inertial odometry, and state estimation algorithms.
- Own the front-end: feature detection and tracking, data association, outlier rejection, multi-camera and multi-sensor geometry and map matching.
- Own the back-end: EKF and/or factor-graph estimation, tightly-coupled sensor fusion, loop closure and relocalization, consistency and observability analysis.
- Support integration and flight testing, debug from real flight data, and feed what you learn in the field back into the algorithms.
- Write efficient and optimized production C++ code.
- Contribute to architecture decisions, code reviews, and the technical growth of the team.
What you'll bring
Required
- MSc or PhD in Computer Science, Robotics, Engineering, or a related field, or a BSc with equivalent hands-on experience.
- 3+ years developing perception and state estimation algorithms for real-time robotic