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- Tasks: Design and deploy cutting-edge computer vision pipelines for impactful 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 innovative projects that shape the future of computer vision in business.
- Qualifications: Experience in computer vision systems and strong Python skills required.
- Other info: Work in a dynamic environment with opportunities for career growth and autonomy.
The predicted salary is between 43200 - 72000 £ 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 (including bank holidays).
- The opportunity to work on technically challenging, high-impact systems that directly influence business performance.
Lead Computer Vision Engineer employer: OpenSource
Contact Detail:
OpenSource Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Computer Vision Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your computer vision projects, especially those that demonstrate your ability to handle messy real-world data. This will give you an edge and show employers what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python and CV/ML libraries, and think about how you can contribute to automating workflows and improving systems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Lead Computer Vision Engineer
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, especially any hands-on work with object detection or tracking. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific projects where you've built or deployed computer vision pipelines. We love seeing real-world applications of your work, so don’t hold back on the details! This helps us understand your problem-solving approach.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you’re passionate about computer vision and how you can contribute to our mission. We appreciate a personal touch, so let your personality come through!
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 the role. Plus, it’s super easy to do!
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, or TensorFlow. Be ready to discuss your hands-on experience with these tools and how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of messy real-world problems you've tackled. Highlight how you approached these challenges, the solutions you implemented, and the impact they had on the business outcomes.
✨Understand the Business Impact
Research the company’s focus on advanced video analytics and think about how your work can influence their business performance. Be prepared to discuss how you can shape the application of computer vision across their operations.
✨Demonstrate Leadership and Ownership
As a Lead Engineer, you'll need to show that you can take ownership of systems from design to deployment. Prepare to talk about your experience making architectural decisions and guiding teams through technical challenges.
