Principal Machine Learning Engineer Live Sports Insights

Descripción del puesto

We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports—giving fans control, fresh perspectives, and predictive insights during the action. As a Principal Machine Learning Engineer ,you’llshape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer the hybrid working approach with 2 days a week onsite in Osterley office . What?you’ll?do: You’ll?be the technical lead for a critical ML domain (e.g.,? live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution—not just single models—while mentoring engineers and data scientists and raising the bar across teams.? Lead the?end-to-end?development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams.? Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment.? Integrate?model?driven?insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and?appropriate use?of data.? Define