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- Tasks: Design and deploy cutting-edge computer vision pipelines for video analytics.
- Company: Join a data-driven tech company revolutionising video insights.
- Benefits: Enjoy a competitive salary, bonuses, private health insurance, and generous leave.
- Why this job: Lead impactful projects and shape the future of computer vision technology.
- Qualifications: Proven experience in computer vision systems and strong Python skills.
- Other info: Autonomy, technical leadership, and excellent career growth opportunities await you.
The predicted salary is between 36000 - 60000 £ per year.
We’re partnering with a data-driven technology company that’s investing heavily in advanced video analytics. They’re looking for a Lead Computer Vision Engineer to join a growing data function and take ownership of how large-scale video data is transformed into structured, high-value insights. This is a high-impact role sitting at the intersection of computer vision, data engineering, and applied analytics. You’ll be the most senior CV specialist in the organisation, setting technical direction and helping move an existing semi-manual workflow towards a highly automated, reliable, production-grade pipeline.
If you enjoy solving messy real-world problems, owning systems end to end, and seeing your work directly influence business outcomes, this role offers a lot of autonomy and responsibility.
Tasks- Designing, building, and deploying production-ready computer vision pipelines that extract structured events and signals from long-form, variable-quality video footage.
- Scaling and automating processing systems across large archives of historical video, while also supporting near-real-time use cases.
- Reducing manual intervention by identifying opportunities for automation and system improvement.
- Defining validation frameworks, metrics, and monitoring to ensure model accuracy and reliability.
- Working closely with domain experts to define rules, edge cases, and quality thresholds.
- Acting as the technical authority for computer vision, influencing architecture, standards, and long-term strategy.
- End-to-end ownership: Take systems from early design through to deployment, monitoring, and iteration.
- Technical leadership: Own architectural decisions and guide the evolution of the computer vision platform.
- Quality and reliability: Build robust validation and monitoring to ensure outputs can be trusted at scale.
- Strategic impact: Shape how computer vision is applied across the business as the function matures.
- Proven commercial experience building and deploying computer vision systems in production.
- Strong hands-on experience in areas such as object detection, tracking, temporal event detection, pose estimation, or action recognition.
- Excellent Python skills and experience with common CV/ML libraries such as OpenCV, PyTorch, or TensorFlow.
- Experience owning technical and architectural decisions for data-intensive systems.
- A pragmatic, delivery-focused mindset with the ability to balance experimentation and production reliability.
- Experience working with noisy, imperfect real-world video data (e.g. broadcast or user-generated footage).
- Exposure to MLOps practices and tooling for deploying and monitoring models at scale.
- Familiarity with sports, media, or broadcast video analytics.
- Up to 30% bonus.
- Enhanced pension contributions.
- Private health insurance and life assurance.
- Sabbatical option after five years.
- 33 days’ annual leave.
Lead Computer Vision Engineer in London employer: OpenSource
Contact Detail:
OpenSource Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Computer Vision Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your computer vision projects. Whether it's GitHub repos or a personal website, let your work speak for itself and demonstrate your expertise.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and case studies related to computer vision. Practice explaining your thought process clearly, as communication is key in these roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Lead Computer Vision Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Computer Vision Engineer role. Highlight your experience with computer vision systems, Python skills, and any relevant projects that showcase your ability to handle large-scale video data.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about computer vision and how your background aligns with the company's goals. Don’t forget to mention specific experiences that demonstrate your problem-solving skills.
Showcase Your Technical Skills: In your application, be sure to highlight your hands-on experience with libraries like OpenCV, PyTorch, or TensorFlow. Mention any projects where you’ve built or deployed production-ready pipelines, as this will show us you’re ready for the challenges ahead.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates regarding your application status!
How to prepare for a job interview at OpenSource
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest computer vision technologies and frameworks like OpenCV, PyTorch, and TensorFlow. Brush up on your Python skills and be ready to discuss specific projects where you've built or deployed CV systems.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled messy real-world problems in previous roles. Be ready to explain your thought process and the impact your solutions had on business outcomes, especially in terms of automation and system improvements.
✨Understand the Business Context
Research the company’s focus on video analytics and think about how your role as a Lead Computer Vision Engineer can influence their strategic goals. Be prepared to discuss how you would shape the application of computer vision across the business.
✨Prepare for Technical Leadership Questions
As the most senior CV specialist, you'll need to demonstrate your ability to make architectural decisions. Think about past experiences where you’ve guided teams or influenced technical direction, and be ready to share those stories.
