About Lúnasa:

Lúnasa is a UK-based space-tech start-up building autonomous satellite navigation solutions to provide safe, sustainable, and affordable satellite operations for the in-space economy. The company has received multiple contracts from the UK Space Agency and the European Space Agency to build an AI-based satellite rendezvous proximity operations (RPO) technology and set to demonstrate the innovation in space by 2024. Lúnasa is also incubated in the European Space Agency and backed by world-class Deep-Tech investors.

Location: London
Salary: Competitive
This position is for a candidate who has the right to work in the UK.

Job Summary:
Lúnasa is seeking a Computer Vision engineer who will support the development with definition, design, analysis, and implementation of the visual navigation architecture related to our satellite Rendezvous Proximity Operations (RPO) Kit. The successful applicant will be responsible for all stages of the algorithm lifecycle, from building low-level architecture, training, simulating, to testing in real-life environment (upcoming space mission). The Computer Vision Engineer will also be involved in detailed technical analysis and testing of the systems and performance, including producing development plans and reports, and other technical reviews internally and with external stakeholders.

Key Skills and Experience:

• 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 applications including active/passive marker design, drive continued development, and integrate robust solutions into products.
• Working experience of mixing image data from different sources; real and synthetic. This is key to leveraging images generated by our in-house built digital twin.
• Background in Machine Learning with experience in large scale training and evaluation of deep convolutional and/or recurrent neural network and/or GANs.