At a Glance
- Tasks: Lead the development of ML systems for real-time sports insights and personalisation.
- Company: Join a leading global streaming platform transforming live sports experiences.
- Benefits: Competitive pay, flexible remote work, and opportunities for mentorship.
- Other info: Dynamic role with excellent growth potential in a fast-paced environment.
- Why this job: Make a real impact on millions of users with cutting-edge AI technology.
- Qualifications: Strong experience in production ML systems and real-time data.
The predicted salary is between 70000 - 90000 € 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
(This isn’t a research role — it’s production, scale, and real-world impact)
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.
Senior Machine Learning Engineer (Fully Remote) in London employer: 5V Video
Join a leading global streaming platform that is revolutionising the way fans engage with live sports through cutting-edge AI technology. As a Senior Machine Learning Engineer, you will enjoy a fully remote work environment with the flexibility of hybrid collaboration, while having the opportunity to take ownership of impactful ML systems that serve millions of users. The company fosters a culture of innovation and mentorship, providing ample opportunities for professional growth and development in a dynamic and fast-paced industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer (Fully Remote) 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 even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your ML projects, especially those related to real-time data or sports. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on relevant tech and concepts. Be ready to discuss your experience with low-latency systems and how you've tackled challenges in production environments. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the quickest way to get noticed and put your application in front of the right people. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Senior Machine Learning Engineer (Fully Remote) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your experience with real-time data and ML systems, as this is what we’re really looking for!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re passionate about transforming live sports with AI. Share specific examples of your work in ML and how it relates to our mission at StudySmarter.
Showcase Your Projects:If you've worked on any relevant projects, especially those involving real-time insights or low-latency systems, make sure to include them. We love seeing practical applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the quickest way to get your application in front of us, and we can’t wait to see what you bring to the table!
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 manage CI/CD and model monitoring in a real-time environment.
✨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 ML systems that deliver insights during live events, as this is crucial for the role.
✨Understand Sports Data
Since the role focuses on sports, having a deep understanding of sports data is key. Familiarise yourself with event tracking and video analysis, and be prepared to discuss how you can leverage this knowledge in your ML solutions.
✨Demonstrate Leadership Skills
They’re looking for someone who can mentor and set technical direction. Think of instances where you’ve led teams or projects, and be ready to share how you can guide others in building scalable ML systems.
