EU remote
Staff Perception
About this role
Join SE3 Labs as Staff Computer Vision Engineer - Perception Take on SE3's hardest perception problems as a hands-on technical leader, and ship systems that work on real missions. About SE3 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 Perception team , 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.
About the Role As Staff Computer Vision Engineer - Perception , you'll set technical direction for SE3's perception stack across object detection, tracking, semantic segmentation and depth estimation, and spend around 80% of your time building it yourself. You'll work closely with our perception lead, founders and autonomy engineers, shaping architecture and core algorithmic decisions without people-management responsibility.
Your work moves from recorded data to field trials and determines how well our platforms understand their surroundings. What You’ll Work On Architecture & Algorithms: Shape the architecture of the perception stack and drive core algorithmic decisions together with the team lead. Detection & Tracking: Build object detection and multi-object tracking that stay reliable on real mission data. Segmentation & Depth: Develop semantic segmentation and depth estimation that give downstream autonomy a dependable picture of the scene.
Evaluation & Replay: Design the evaluation and replay loop so the team iterates mostly on recorded data, with clear metrics, benchmark datasets and regression tests. Real-World Deployment: Optimize models for onboard compute and take them through field trials until they work under real operating conditions. Technical Roadmap: Contribute to the perception roadmap by identifying the problems that matter most for field performance.