Overview
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.
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