Machine Learning Engineer

Contract : Full-Time, Permanent

Working Location : Hybrid, 2 Days a week in the office, minimum

Office Locations : Hungary

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 Computer Vision and ML teams to develop, adapt, and deploy end-to-end tracking solutions for sports officiating and analytics
• Implement and optimize ML models (both real-time and offline) using Python, C++, PyTorch, NumPy, Pandas, and OpenCV
• Design and build ETL pipelines and data manipulation workflows, optimizing pipelines for scale and reproducibility
• Deploy models to existing production pipelines and APIs using deployment frameworks and techniques like TensorRT, ONNX, quantization, and profiling
• Implement ML solutions based on relevant research papers and evaluate experimental results to adapt existing models for improved performance
• Consistently write clean, testable, readable, and maintainable code, actively participating in peer code reviews and debugging

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related fields
• Demonstrated experience as an ML Engineer or Applied Scientist, autonomously delivering end-to-end solutions into production
• Proficiency in Python, alongside core ML/CV frameworks (PyTorch, NumPy, Pandas, OpenCV)
• Solid foundation in statistical methods, optimization algorithms, and ML fundamentals
• Hands-on experience implementing reproducible ML pipelines, ETL processes, and model deployment via tools like TensorRT or ONNX
• Ability to break down complex problems into clear technical solutions and communicate them effectively in simple language

Nice to Haves:

• Experience with modern C++ (C++17/20), CUDA, CMake & Visual Studio, OpenCV, Typescript & Semantic UI React, and SSH
• Experience with QT, TeamCity, JIRA & Kanban, and Confluence

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
• Collaboration & Knowledge Sharing – We communicate complex ideas clearly and support one another through constructive feedback and code reviews
• 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

Equal Opportunity Employer 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!