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A leading sports technology company seeks a Machine Learning Engineer to innovate in real-time tracking solutions for sports officiating and broadcasting. You will collaborate with cross-functional teams, design machine learning models, and engage in a hybrid working environment with minimum office attendance. The role values autonomy, collaboration, and continuous learning, offering competitive benefits including an enhanced pension scheme and wellness initiatives.
Salary Banding: Between £40,000 and £55,000 per annum
Contract: Full-Time, Permanent
Working Location: Hybrid, 2 Days a week in the office, minimum
Office Locations: Basingstoke, London, Bristol
Hawk-Eye Innovations is a leading sports technology company that delivers real‑time, end‑to‑end solutions for tracking balls, players, and other relevant sports objects. Our products are used for sports officiating and data analytics purposes, including SkeleTRACK, a real‑time ball and skeletal tracking technology deployed in major US sports leagues and European football leagues.
As a Machine Learning Engineer at Hawk‑Eye Innovations, you will be part of an agile team responsible for the end‑to‑end pipeline of our machine learning models. You will work closely with our Computer Vision Engineering team to innovate and build incredible ball and player tracking solutions for sports officiating, broadcast video, coaching, and fan engagement. Your role will involve designing and building new ML models, and maintaining modern architecture and design practices.
At Hawk‑Eye, our culture is built on openness, collaboration, and technical excellence. Here’s what we value in our team members:
Hawk-Eye is committed to fostering an inclusive and diverse workplace. We ensure all employees are treated fairly, regardless of gender, marital status, race, nationality, religion, age, disability, or union membership status. We value diversity and strive to create an environment where everyone can reach their full potential.
This is a fantastic opportunity to join Hawk‑Eye Innovations and make a significant impact in the sports technology industry. If you’re excited about solving complex ML problems in real‑time and seeing your work on the world’s biggest sporting stages, we’d love to hear from you!