Computer Vision Engineer
Lúnasa is a fast-growing space start-up based in Harwell and London with a mission to develop an innovative, dual-stage in-space satellite servicing vehicle to provide affordable access to new orbits for SmallSats and ultimately satellite life extension services in Earth orbits and beyond. We are a venture funded company, incubated in ESA Business Incubation Centre (Harwell), and recognised by the UK Space Agency.
Lúnasa is seeking a Computer Vision engineer who will support our development with definition, design, analysis, and implementation of the visual navigation architecture related to the satellite rendezvous proximity operations and docking (RPOD) mission, powered by the intelligent vision-based navigation system in development at Lúnasa. The successful applicant will be involved in the definition and analysis of the system requirements for Lúnasa’s in-orbit servicing vehicle, including close proximity and docking applications.
Location: Harwell and/or London
- Design and develop novel computer vision and/or Machine Learning algorithms in areas such as: real-time scene and rigid object tracking, space object detection, 6 DoF pose estimation, key point estimation, and depth sensing.
- Develop prototypes for a Computer Vision subsystem for spacecraft guidance and navigation control applications including active/passive marker design, drive continued development, and integrate robust solutions into products.
- Collaborate with Lúnasa’s Guidance, Navigation, and Control engineering and research teams in Computer Vision, Machine Learning, and graphics (Digital Twin).
- Be able to create and implement product development and testing plans.
- BSc degree in Computer Science, Computer Vision, Machine Learning, or related degrees
- 3+ years of experience developing and designing computer vision and/or machine learning technologies and systems
- Working knowledge of Python and C++
- Prototyping and engineering experience in at least one relevant specialisation area in either Computer Vision or Machine Learning: Marker-based rigid body pose estimation, Extended Kalman Filter for Rigid Body Pose Estimation, SLAM, State Estimation Sensor Fusion, Dense 3D reconstruction, object detection, segmentation and tracking scene understanding/ Semantic segmentation, Photorealistic rendering, Camera calibration.
- MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field.
- 2+ years of industry experience working on projects such as Marker-based rigid body pose estimation, Extended Kalman Filter for Rigid Body Pose Estimation, real-time SLAM and 3D reconstruction, sensor fusion and active depth sensing, object tracking and rigid body pose estimation, and/or image processing. Image and/or semantic segmentation, 2D and 3D keypoint estimation, and surface reconstruction, depth estimation, generative methods such as GANs, or photorealistic rendering.
- Developing and designing Computer Vision and/or Machine Learning technologies and systems for running on real-time embedded systems such as autonomous vehicle control, aircraft/drone guidance, navigation, and control.
- Background in Machine Learning with experience in large scale training and evaluation of deep convolutional and/or recurrent neural networks and/or GANs.
What we provide