Summary: Join a leading drone technology company to strengthen the perception pipeline of Detect and Avoid systems using geometric computer vision techniques. Highlights: 1. Contribute to cutting-edge drone technology and R&D development. 2. Work with computer vision techniques for perception systems in drones. 3. Be part of a mission-driven team enabling drones to populate our skies. Alicante, España **\#Join us in enabling drones to populate our skies** At **Embention**, we have been driven since 2007 by a clear mission: **Enabling drones to populate our skies.** We provide more than **700 customers in 70 countries** including internationally renowned companies such as Toyota, Amazon Prime Air, and Honda with Veronte autopilots, critical avionics, and software for their professional drones and eVTOLs. All our systems are developed in accordance with DO\-178C, DO\-254, and DO\-160 standards, making us the only company in the sector certified by AESA and EASA as both a POA and APDOA. The core of our company lies in our R\&D team, made up of over 100 multidisciplinary engineers. Together with the rest of the organization, we are a team of **180 professionals** united by a single goal: to innovate and push the boundaries of UAV technology. Following a record\-breaking 2025 marked by strong stock market performance, the launch of industrial production in the United Arab Emirates, and the establishment of a subsidiary in the United States, we are looking to continue expanding our team and driving continuous R\&D development. If you are passionate about our mission and want to be part of this journey, we are looking for you. **What would be your mission?** Your mission will be to strengthen the perception pipeline of the Detect and Avoid system using geometric computer vision techniques, ensuring spatial consistency and reliability of detections in BVLOS operations. **Which will be your responsibilities?*** Design and maintain the geometric validation module of the perception system. * Ensure the spatial and temporal consistency of detections generated by the AI model. * Extract and validate relevant structural information from the scene to reinforce the reliability of detections. * Estimate relative motion between ownship and intruders from image sequences. * Contribute to the robust calculation of dynamic metrics such as Time\-To\-Collision (TTC). * Reject inconsistent or spurious detections through geometric validation. * Evaluate the applicability of pose estimation and reconstruction techniques when they provide operational value. * Merge geometric information with the output of the AI\-based detector to improve stability and reduce false positives. * Optimise system behaviour under real\-time constraints. **️‍ ️ What do we need?*** Training in computer engineering, telecommunications or similar. * Experience in OpenCV, C\+\+ or Python. **What do we value?*** Classical computer vision. * Epipolar geometry. * Projective geometry. * Pose estimation. * Multi\-view reconstruction. * SVD and its numerical properties. * RANSAC. * Bundle adjustment. * Iterative methods such as Levenberg\-Marquardt. * Optical flow (Lucas\-Kanade). * Experience in embedded applications or autonomous systems. ***Embention is an equal opportunity employer. Recruitment decisions are made based on experience, qualifications, and alignment with role requirements.*** ***Want to meet the team?***