Principle Machine Learning Engineer

Most sports data is reactive – stats after the moment’s gone.

This role is about building systems that generate real-time insights during live sport.

Why This Role?

• Leading global streaming / sports platform
• Real ownership of ML systems at scale (millions of users)
• Solving complex real-time + low latency AI problems

The Company / Product

You’ll be working on a cutting-edge platform transforming how fans experience live sport using AI to deliver personalised insights, predictions, and real-time data during live events.

What You’ll Be Working On

• Leading development of ML systems for live sports insights + personalisation
• Building solutions across Computer Vision, ML, and Generative AI
• Turning live video + sports data into real-time predictions and insights
• Driving end-to-end MLOps (CI/CD, monitoring, retraining, deployment)
• Integrating ML outputs into personalisation engines
• Owning experimentation, A/B testing, and performance metrics
• Mentoring engineers and setting technical direction across teams
• Python
• PyTorch / TensorFlow
• Real-time / streaming systems
• Cloud-based ML infrastructure

What You’ll Bring

• Strong experience building production ML systems at scale
• Experience working with real-time or streaming data
• Deep understanding of sports data (event, tracking, or video)
• Hands‑on experience taking models from research → production
• Strong technical leadership and mentoring experience

Ideal Profiles

• Principal / Staff ML Engineers in streaming, sports, or media
• ML Engineers from real-time / low-latency environments
• Engineers working on computer vision, personalisation, or live data systems

(This isn’t a research role — it’s production, scale, and real-world impact)

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