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- Tasks: Lead the development of ML systems for real-time sports insights and personalisation.
- Company: Join a leading global streaming platform transforming live sports with AI.
- Benefits: Competitive pay, hybrid work model, and opportunity to make a real impact.
- Other info: Mentor engineers and drive technical direction in a dynamic environment.
- Why this job: Own ML systems at scale and solve complex, low-latency AI challenges.
- Qualifications: Experience in building production ML systems and working with real-time data.
The predicted salary is between 80000 - 100000 £ per year.
This role is about building systems that generate real-time insights during live sport.
Why This Role?
- Leading global streaming / sports platform
- Real ownership of ML systems at scale (millions of users)
- Solving complex real-time + low latency AI problems
The Company / Product
You’ll be working on a cutting-edge platform transforming how fans experience live sport using AI to deliver personalised insights, predictions, and real-time data during live events.
What You’ll Be Working On
- Leading development of ML systems for live sports insights + personalisation
- Building solutions across Computer Vision, ML, and Generative AI
- Turning live video + sports data into real-time predictions and insights
- Designing low-latency, high-scale ML systems in production
- Driving end-to-end MLOps (CI/CD, monitoring, retraining, deployment)
- Integrating ML outputs into personalisation engines
- Owning experimentation, A/B testing, and performance metrics
- Mentoring engineers and setting technical direction across teams
Tech Stack
- Python
- PyTorch / TensorFlow
- MLOps (CI/CD, model monitoring, retraining pipelines)
- Real-time / streaming systems
- Cloud-based ML infrastructure
What You’ll Bring
- Strong experience building production ML systems at scale
- Experience working with real-time or streaming data
- Deep understanding of sports data (event, tracking, or video)
- Hands-on experience taking models from research → production
- Strong technical leadership and mentoring experience
Ideal Profiles
- Principal / Staff ML Engineers in streaming, sports, or media
- ML Engineers from real-time / low-latency environments
- Engineers working on computer vision, personalisation, or live data systems
No need for a perfect CV if you’ve built ML systems that run in production, let’s talk. I can get you directly in front of the team quickly.
Principle Machine Learning Engineer in London employer: 5V Video
Contact Detail:
5V Video Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principle Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at the company you're eyeing. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to ML systems, make sure to highlight them. Real-world examples of your work can speak volumes more than a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of real-time data processing and MLOps. Practise explaining your past projects and how they relate to the role – clarity is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the quickest way to get noticed, and we’re keen to see candidates who are genuinely interested in transforming live sports with AI.
We think you need these skills to ace Principle Machine Learning Engineer in London
Some tips for your application 🫡
Show Your Passion for Sports and Tech: When you're writing your application, let your love for sports and technology shine through. We want to see how your experience aligns with our mission of transforming live sports using AI. Share any relevant projects or experiences that highlight your enthusiasm!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this role. Highlight your experience with real-time data, ML systems, and any specific technologies mentioned in the job description. We appreciate when candidates take the time to connect their skills directly to what we’re looking for.
Be Clear and Concise: Keep your application straightforward and to the point. We’re looking for clarity in your communication, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and how you can contribute to our team.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company and culture while you’re at it.
How to prepare for a job interview at 5V Video
✨Know Your Tech Stack
Make sure you’re well-versed in Python, PyTorch, and TensorFlow. Brush up on your MLOps knowledge too, as they’ll want to see how you can drive CI/CD and model monitoring in production.
✨Showcase Real-Time Experience
Prepare examples of your work with real-time or streaming data. Be ready to discuss specific projects where you’ve built low-latency ML systems and how they impacted user experience.
✨Understand Sports Data
Since this role revolves around sports insights, demonstrate your understanding of sports data, whether it’s event tracking or video analysis. Share how you’ve used this knowledge to create impactful ML solutions.
✨Highlight Leadership Skills
This position involves mentoring and setting technical direction, so be prepared to talk about your leadership experiences. Discuss how you’ve guided teams through complex projects and fostered a collaborative environment.