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- Tasks: Lead AI-driven projects to enhance real-time sports experiences for millions of fans.
- Company: SoTalent, a leader in innovative sports technology.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Shape the future of sports with cutting-edge AI technology and make a real impact.
- Qualifications: Proven experience in ML systems, strong Python skills, and leadership abilities.
- Other info: Join a dynamic team in a modern campus environment focused on tech and data.
The predicted salary is between 36000 - 60000 £ per year.
AI Engineering Manager – Sports & Real-Time Intelligence, London (Hybrid)
Lead the development of AI-driven, real-time sports experiences used by millions of fans. This role sits at the intersection of machine learning, computer vision, streaming data, and personalisation, shaping how live sport is analysed, understood, and experienced.
About The Role
As AI Engineering Manager, you’ll own the technical direction for a critical ML domain within live sports—such as real-time insights, personalisation, ranking, or computer vision for multi-angle video. You’ll define architecture, influence roadmaps, and lead teams delivering production-grade ML systems, not just experimental models. You’ll mentor engineers and data scientists, establish strong MLOps practices, and ensure AI solutions are scalable, ethical, and reliable during peak live events.
Responsibilities
- Act as technical lead for a key AI/ML domain, shaping architecture, standards, and delivery across teams
- Lead end-to-end development of AI solutions using Machine Learning, Computer Vision, Generative AI, and data science
- Build systems that generate real-time sports insights, including automated metadata, event detection, player performance analytics, and injury risk indicators
- Integrate model-driven insights into personalisation engines, tailoring experiences based on teams, players, and match context
- Define experimentation strategies, lead A/B testing, and own metrics, dashboards, and performance monitoring
- Establish and operate robust MLOps pipelines, covering CI/CD, model registries, drift detection, retraining, and observability
- Design and run low-latency, highly resilient cloud-based AI systems capable of handling live sports traffic at scale
- Embed responsible and ethical AI principles from design through deployment
What you’ll bring
- Proven lead-level engineering experience delivering production ML systems in sports, media, or other real-time data domains
- Deep hands-on experience with sports data (event, tracking, video, or high-volume time-series data) and turning it into actionable insights
- Strong understanding of modern ML approaches, including Generative AI and multimodal data (numerical, spatial, video, metadata)
- Advanced Python skills and hands-on experience with ML/DL frameworks such as PyTorch or TensorFlow, taking models from prototype to production
- End-to-end MLOps expertise, including experiment tracking, automated deployment, monitoring, and infrastructure-as-code
- Experience designing scalable, low-latency architectures, including real-time or near-real-time streaming systems
- Demonstrated technical leadership, mentoring senior and mid-level engineers and data scientists
- Strong communication skills, able to clearly explain complex AI strategies to technical and non-technical stakeholders
Ways of working
- Hybrid working model combining office collaboration and remote flexibility
- Modern campus environment with strong tech, data, and product communities
Why this role?
This is a rare opportunity to lead AI at scale in live sports, where milliseconds matter and models operate in real time. You’ll influence platform direction, raise engineering standards, and help redefine how fans experience sport through intelligent, personalised technology.
AI Engineering Manager (Machine Learning) - SoTalent in London employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineering Manager (Machine Learning) - SoTalent in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. The more you engage with others, the better your chances of landing that AI Engineering Manager role.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving machine learning and real-time data. This will help us see your capabilities in action.
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice explaining complex ideas simply, as you'll need to communicate effectively with both techies and non-techies alike.
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AI Engineering Manager (Machine Learning) - SoTalent in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of AI Engineering Manager. Highlight your experience with machine learning, computer vision, and real-time data systems. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for sports and technology, and explain why you’re the perfect fit for this role. Let us know how you can lead our AI initiatives and make a difference.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work with ML systems, especially in sports or real-time applications. We love seeing practical examples of your expertise.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss any important updates. Plus, it’s super easy!
How to prepare for a job interview at Jobster
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning techniques, especially those relevant to sports data. Brush up on your Python skills and be ready to discuss frameworks like PyTorch or TensorFlow. Being able to explain how you've taken models from prototype to production will definitely impress.
✨Showcase Your Leadership Skills
As an AI Engineering Manager, you'll need to demonstrate your ability to lead teams effectively. Prepare examples of how you've mentored engineers and data scientists in the past. Highlight your experience in establishing MLOps practices and how you've influenced technical direction in previous roles.
✨Understand the Business Impact
Be ready to discuss how your work in AI can enhance real-time sports experiences. Think about how you can turn complex data into actionable insights that improve fan engagement. Showing that you understand the intersection of technology and user experience will set you apart.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on your knowledge of low-latency architectures and real-time streaming systems. Be prepared to talk about your approach to A/B testing and performance monitoring, as these are crucial for the role.
