Overview
As a Principal Machine Learning Engineer you will shape 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.
Responsibilities
- Lead the end‑to‑end development of AI solutions using Computer Vision, Machine Learning, Generative AI and data science for automated sports metadata generation and key event detection in live content and data streams.
- Design models that generate actionable player performance insights, contextual statistics and injury risk assessments, embedding 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 data use.
- Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices and own end‑to‑end productionisation from data ingestion through deployment and ongoing model monitoring.
- Design, architect and operate low‑latency, highly reliable cloud‑based AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time and an optimal balance between cost, latency and scale.
What You’ll Bring
- Proven, extensive lead‑level engineering experience delivering data‑driven ML systems with clear ownership of technical direction, mentoring and delivery.
- Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (numerical, spatial, video, metadata).
- Advanced Python expertise with strong hands‑on use of machine‑learning frameworks such as PyTorch and TensorFlow, taking models from experimentation into production model serving.
- End‑to‑end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining and infrastructure‑as‑code practices.
- Proven technical leadership experience that includes mentoring and guiding Senior and Mid‑Level Data Scientists in day‑to‑day work and career development, demonstrating adaptability in a fast‑changing environment.
Nice to Have
- Understanding of sports data, including hands‑on experience with event data, tracking data or high‑volume sports datasets, converting them into actionable analytical or predictive insights.
- Enthusiasm for sports, with a passion to push the sports experience to the next level.
The Rewards
- Sky Q – the TV you love all in one place
- Exclusive access to Sky Glass at a discounted rate
- A generous pension package
- Private healthcare
- Discounted mobile and broadband services
- A wide range of Sky VIP rewards and experiences
Inclusion & How You’ll Work
We are a Disability Confident Employer and welcome and encourage applications from all candidates. We will ensure a fair and consistent experience for everyone and make reasonable adjustments to support you where appropriate. We embrace hybrid working, combining office time in Osterley with the convenience of working from home.
Your Office Space – Osterley
Our Osterley Campus is a 10‑minute walk from Syon Lane train station and offers free shuttle buses to nearby tube stations. On campus you’ll find subsidised restaurants, cafes, a Waitrose, a gym, a cinema, a car wash and more.
Background Check
Successful applicants may be asked to complete a criminal record check, and offers may be withdrawn if convictions are incompatible with the role.
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