Machine Learning Engineer

Hawk-Eye Innovations

Bristol, England, United Kingdom

Bristol, England, United Kingdom

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Über

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 Join Our Team as a Machine Learning Engineer at Hawk-Eye Innovations 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. Key Responsibilities
Work closely with our Computer Vision Engineering team to develop and deploy innovative ball and player tracking solutions Design and build new ML models, both real-time and otherwise, using Python and relevant libraries such as Pytorch, Pytorch-ignite, Numpy, Jupyter, and Pandas Maintain strong relationships within the machine learning team and communicate effectively with both the engineering and product teams Use cloud and containerised systems for model training, testing and deployment Develop and maintain MLOps and CI/CD pipelines Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related fields Previous experience in machine learning, computer vision, or related fields Strong programming skills in Python and experience with relevant libraries such as Pytorch, Pytorch-ignite, Numpy, Pandas and Matplotlib Strong knowledge of Git Strong problem-solving skills and ability to work in an agile environment Good communication skills and ability to work collaboratively with cross-functional teams Nice to Haves
Experience with modern C++ (C++17/20), CUDA, TensorRT, ClearML, CMake & Visual Studio, OpenCV, Typescript & Semantic UI React What We Value
At Hawk-Eye, our culture is built on openness, collaboration, and technical excellence. Here’s what we value in our team members: Autonomy & Accountability – We trust our engineers to own their work and deliver impact Mentorship & Leadership – As a senior team member, you’ll lead by example and uplift others Pragmatism – We’re creative and experimental, but always grounded in real-world application Continuous Learning – From peer code reviews to hack days and conferences, we never stop growing Collaboration – We work cross-functionally and communicate with transparency and empathy Reward, Benefits, And Wellness
Annual Leave: 25 days + 8 public holidays Enhanced Pension Scheme: 5% matching Flexible Working: Hybrid model (2 days in the office per week) Wellness: Complimentary Unmind app, onsite gym (Basingstoke) Exclusive Perks: Access to sporting events and tickets, Sony Group Company discounts Equality and Opportunity
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. Apply Today! 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!
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Bristol, England, United Kingdom

Sprachkenntnisse

English

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