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- Tasks: Lead the development of computer vision systems from R&D to production.
- Company: Join a high-growth startup transforming sports analytics with AI.
- Benefits: Enjoy remote work flexibility and quarterly meetups in London.
- Other info: Be part of a fully backed startup with real autonomy and ownership.
- Why this job: Work on innovative projects at the intersection of AI, video, and sports science.
- Qualifications: Experience with deep learning, PyTorch, TensorFlow, and mentoring engineers.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Job Description
I am searching for a Lead Computer Vision Engineer to join a high-growth startup revolutionizing sports analytics using AI. They're backed by serious investor support and building transformative tech that’s changing how elite-level performance is understood and optimized.
You’d lead the charge on computer vision systems—from R&D to production-ready deployment—alongside a sharp engineering and product team. If you're excited by deep learning, real-time processing, and building 0–1 systems with impact, this is worth a look.
đź“Ť Location: Remote (with quarterly London meetups)
đź’Ľ Mission: Redefining how performance is measured using cutting-edge vision systems
đź’ˇ Why join?
- Lead innovative projects at the intersection of AI + video + sport science
- Fully backed startup with funding and traction
- Remote-first culture with real autonomy and ownership
🚀 Your Role:
- Build and optimize vision models (object tracking, pose estimation, segmentation)
- Take prototypes to production with PyTorch, TensorFlow, Docker
- Drive product development and mentor other engineers
- Collaborate across product, data, and engineering for real-world deployment
Apply now!
Lead Computer Vision Engineer employer: Understanding Recruitment
Contact Detail:
Understanding Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Computer Vision Engineer
✨Tip Number 1
Network with professionals in the sports analytics and AI fields. Attend relevant meetups or webinars to connect with like-minded individuals and industry leaders who might provide insights or referrals for the Lead Computer Vision Engineer position.
✨Tip Number 2
Showcase your expertise in computer vision by contributing to open-source projects or publishing articles on platforms like Medium. This not only demonstrates your skills but also helps you build a portfolio that can impress potential employers.
✨Tip Number 3
Stay updated on the latest trends and technologies in AI and computer vision. Follow influential researchers and companies in the field on social media, and engage with their content to show your passion and knowledge during interviews.
✨Tip Number 4
Prepare to discuss real-world applications of your work in computer vision, especially in sports analytics. Think of specific examples where your contributions have led to measurable improvements, as this will resonate well with the startup's mission.
We think you need these skills to ace Lead Computer Vision Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in computer vision, deep learning, and any specific technologies mentioned in the job description, such as PyTorch and TensorFlow. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sports analytics and AI. Discuss how your previous projects align with the company's mission of redefining performance measurement and mention any leadership experience you have in similar roles.
Showcase Relevant Projects: If you have worked on projects involving object tracking, pose estimation, or segmentation, be sure to include these in your application. Provide links to your GitHub or portfolio where potential employers can see your work in action.
Highlight Collaboration Skills: Since the role involves collaboration across product, data, and engineering teams, emphasise your teamwork and mentoring experiences. Mention specific instances where you successfully collaborated on projects or guided other engineers.
How to prepare for a job interview at Understanding Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with computer vision technologies, particularly in areas like object tracking, pose estimation, and segmentation. Bring examples of past projects where you've successfully implemented these techniques, ideally using frameworks like PyTorch or TensorFlow.
✨Demonstrate Leadership Experience
As a Lead Computer Vision Engineer, you'll be expected to mentor other engineers and drive product development. Share specific instances where you've led a team or project, highlighting your ability to inspire and guide others towards achieving common goals.
✨Understand the Company’s Mission
Research the startup's mission to redefine performance measurement through AI and sports analytics. Be ready to discuss how your skills and experiences align with their goals, and express your enthusiasm for contributing to innovative projects at the intersection of AI and sports science.
✨Prepare for Collaborative Scenarios
Collaboration is key in this role, so think of examples where you've worked effectively with cross-functional teams. Be ready to discuss how you approach collaboration, especially in remote settings, and how you ensure successful communication and project outcomes.