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- Tasks: Lead AI-driven projects to enhance real-time sports experiences for millions of fans.
- Company: Join a cutting-edge tech company at the forefront of sports innovation.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Shape the future of sports with AI technology that makes a real impact.
- Qualifications: Proven experience in ML systems, strong Python skills, and leadership abilities.
- Other info: Be part of a dynamic team redefining how fans engage with live sports.
The predicted salary is between 48000 - 72000 £ per year.
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.
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.
What you’ll do:
- 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 in England employer: SoTalent
Contact Detail:
SoTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Ai Engineering Manager in England
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and sports tech scene. Attend meetups, webinars, or even local events. 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 projects, especially those related to machine learning and real-time data. This is your chance to demonstrate your expertise in building production-grade ML systems and how you’ve tackled challenges in the past.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with MLOps, cloud-based systems, and how you’ve implemented ethical AI practices. Practice explaining complex concepts in simple terms – it’ll impress both technical and non-technical interviewers!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates. So, get your application in and let’s shape the future of sports together!
We think you need these skills to ace Ai Engineering Manager in England
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. We love seeing genuine enthusiasm and a clear understanding of what we do.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your expertise in AI solutions and MLOps practices. We’re keen to see your hands-on experience in action.
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 get the best experience possible. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at SoTalent
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning techniques, especially those relevant to sports and real-time 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 and mentor teams. Prepare examples of how you've guided engineers and data scientists in the past. Highlight your experience in establishing MLOps practices and how you've influenced technical direction in previous roles.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-time scenarios. Think about challenges you've faced in delivering production-grade ML systems and how you overcame them. Be ready to discuss your approach to designing scalable, low-latency architectures and handling peak live events.
✨Communicate Clearly and Confidently
You’ll need to explain complex AI strategies to both technical and non-technical stakeholders. Practice articulating your thoughts clearly and concisely. Use examples from your experience to illustrate your points, ensuring you can convey the importance of ethical AI principles in your work.
