At a Glance
- Tasks: Develop cutting-edge computer vision solutions for autonomous satellite navigation.
- Company: Exciting space-tech start-up revolutionising satellite operations.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Fast-paced environment with a focus on innovation and collaboration.
- Why this job: Join a dynamic team and contribute to groundbreaking space missions.
- Qualifications: Experience in computer vision, Python, and deep learning frameworks required.
The predicted salary is between 36000 - 60000 £ per year.
Lúnasa is a London-based space-tech start-up building next-gen space systems and services 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 and deploy advanced satellite servicing technologies and is set to deploy its first space mission by 2026. Lúnasa is also backed by world-class Deep-Tech investors.
This role is held as hybrid mode of remote and in-person working.
Job Summary
We are looking for an experienced and confident Computer Vision Engineer to join our growing team, supporting our on-going development in autonomous vision-based satellite navigation solutions. This role involves low-level software development using AI/ML techniques, using our in-house built simulators and digital twins for validating the software, integrating software and hardware, and testing using our dark room robotics lab.
What We’re Looking For
- Strong experience in Computer Vision and image processing
- Proficiency in Python for CV/ML applications
- Experience with deep learning frameworks (PyTorch)
- Practical experience deploying ML models on embedded or edge hardware
- Familiarity with Docker and Linux-based development environments
- Strong software engineering practices (version control, testing, documentation)
- Proven, hands-on experience working directly with cameras and imaging systems, including camera configuration, calibration, image acquisition pipelines, and troubleshooting real sensor data
- Experience with space, robotics, autonomy, or safety-critical systems
- Knowledge of pose estimation, SLAM, or visual odometry
- Strong ability to multitask
- Familiarity with synthetic data generation and simulation environments
- Experience with FastAPI or similar backend frameworks
Computer Vision Engineer in London employer: Lúnasa Ltd.
Lúnasa is an exceptional employer, offering a dynamic and innovative work environment in the heart of London. With a strong focus on employee growth and development, team members are encouraged to take initiative and contribute to cutting-edge projects in the space-tech sector. The hybrid working model promotes a healthy work-life balance, while the company's backing from leading Deep-Tech investors ensures exciting opportunities for those looking to make a meaningful impact in the rapidly evolving in-space economy.
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the space-tech industry, especially those working at Lúnasa or similar companies. Attend meetups, webinars, and conferences to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to computer vision and AI/ML. This can be a game-changer during interviews, as it gives potential employers a tangible sense of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding key concepts in computer vision. Practice common interview questions and consider mock interviews to build confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Lúnasa.
We think you need these skills to ace Computer Vision Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Computer Vision Engineer role. Highlight your experience with AI/ML techniques, Python, and any relevant projects that showcase your skills in image processing and deep learning frameworks like PyTorch.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for space-tech and how your background aligns with our mission at Lúnasa. Don’t forget to mention your proactive approach and ability to thrive in dynamic environments.
Showcase Relevant Projects:If you've worked on projects involving cameras, imaging systems, or robotics, make sure to include them in your application. We love seeing hands-on experience, so share any practical applications of your skills, especially in safety-critical systems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Lúnasa. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Lúnasa Ltd.
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of computer vision and image processing. Be ready to discuss your experience with Python, deep learning frameworks like PyTorch, and any hands-on work you've done with cameras and imaging systems. The more specific examples you can provide, the better!
✨Show Off Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous projects, especially those involving low-level software development or deploying ML models. Lúnasa is looking for someone who thrives in dynamic environments, so share how you tackled issues and what you learned from them.
✨Familiarise Yourself with Their Mission
Research Lúnasa's projects and their goals in the space-tech industry. Understanding their mission to provide safe and sustainable satellite operations will help you align your answers with their values and demonstrate your genuine interest in the role.
✨Practice Your Communication Skills
Since this role involves working in a hybrid environment and collaborating with various teams, practice explaining complex technical concepts in simple terms. Being able to communicate effectively will show that you're not just a tech whiz but also a great team player.
