The posting
Overview We are looking for a Computer Vision Engineer to help build and deploy perception systems that run onboard autonomous aerial platforms. This is not offline research. Our algorithms run in real time on embedded computers, in the air, in conditions we do not control.
You will work across classical computer vision, camera integration and validation, calibration and optimization for constrained hardware. You will take your work to the field, fly it, look at the logs and improve it. Our platforms serve both commercial and government customers across applications including inspection, mapping, search and rescue and security.
If you like hard real world problems and short feedback loops between an idea and a flight test, we want to talk with you.
Responsibilities and Duties
- Implement and optimize onboard perception algorithms for real time detection, temporal association and state estimation of dynamic objects from a moving platform.
- Integrate new camera modules onto our platforms and validate them against real requirements: image quality, timing, latency and behavior in the conditions we actually fly in.
- Build repeatable test and evaluation procedures so that camera and algorithm performance is measured rather than judged by eye, and comparable across units, builds and iterations.
- Run and improve camera calibration and sensor synchronization procedures, including multi camera and multi sensor setups.
- Profile and optimize pipelines for embedded inference against explicit latency, throughput and compute budgets, and evaluate or retrain detection models on real captured data.
- Support field test campaigns. Take algorithms and cameras from bench to flight, work alongside pilots and integrators on site and close the loop on real captured data.
- Own your deliverables end to end, contribute input into camera, lens and sensor selection, and keep the team informed on progress and risks.
Qualifications and Skills
- Degree in Computer Science, Electrical Engineering, Robotics or a related field, or equivalent practical experience.
- Experience building computer vision systems, with exposure to resource constrained or embedded platforms.
- Working knowledge of classical computer vision: feature detection and matching, optical flow, camera models and calibration, multiple view geometry.
- Practical experience with cameras as hardware, not just as a source of frames. Sensor and lens behavior, exposure, timing and what goes wrong when a new module arrives.
- Proficiency in C++ and Python, with real experience in OpenCV.
- Evidence of taking a project from problem definition to something that actually ran on hardware, and comfort doing that in the field alongside pilots and real logs.
Nice to have
- Camera bring up below the level of a vendor SDK. MIPI CSI-2, USB or GigE, driver or V4L2 level work.
- Experience with ISP tuning, auto exposure or auto gain pipelines.
- Experience evaluating or retraining detection models on real captured data.
- State estimation and sensor fusion, visual inertial odometry or visual SLAM.
- Experience with ROS2, embedded inference runtimes, or aerial platforms such as PX4 or MAVLink based systems.
Benefits
- Flexible working hours
- Stock Options
- Generous holiday allowance
- Company pension plan
- Car parking
- Enhanced maternity & paternity leave
- Mental health and wellbeing support
- Learning and development opportunities
About Auterion
We are building the leading software platform for AI-powered autonomous systems for enterprise and government customers. Our team is supporting the most important missions and solving the most challenging problems.
At Auterion, we bring together the sharpest minds who love to solve the hardest problems. Join a vibrant team built on innovation, openness, and excellence, where you’ll be empowered to develop ideas, collaborate across all levels, and make an impact that matters.
