Machine Learning Engineer

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Sofascore

WebsiteLinkedInAll Job Openings

201 - 500 employees

⚽ Sports

📱 Media

Sports • Media

Sofascore is a comprehensive platform offering real-time sports scores and updates for a wide range of sports including football, basketball, tennis, and many more. The service features live coverage of over 500 worldwide leagues, cups, and tournaments. It provides updated results, statistics, league tables, video highlights, and fixtures. Sofascore includes features such as player ratings, match statistics, odds, and the ability to track favorite teams and matches. It is a popular destination for sports enthusiasts seeking fast and accurate live score updates and detailed sports data.

📋 Description

• Design, develop, evaluate, and improve machine learning solutions for real product problems used by tens of millions of users worldwide • Work on recommender systems, personalized feeds, semantic search, sentiment analysis, NLP, LLM-powered applications, classical machine learning problems, and potentially computer vision • Own ML problems end-to-end, from understanding business problems and exploring data through model selection, development, evaluation, and system integration • Develop new ML solutions and improve and maintain existing systems • Build LLM-powered solutions and contribute to retrieval-augmented generation and modern NLP systems • Write clean, maintainable, testable, production-quality Python code • Work with large datasets using Python and SQL and build reliable data and model workflows • Evaluate models rigorously, select meaningful metrics, identify overfitting and data leakage, and assess modelling trade-offs • Collaborate with product managers, analysts, software engineers, and stakeholders to translate business needs into ML problems • Select an appropriate level of solution complexity, from heuristics and classical ML to deep learning, recommender systems, or LLM-based approaches • Stay current with machine learning and LLM developments and apply useful techniques

🎯 Requirements

• 2+ years of professional industry experience in a Machine Learning or closely related engineering role • A Master's degree in Computer Science, Software Engineering, Mathematics, Electrical Engineering, Data Science, or another relevant technical or quantitative field • Strong foundations in supervised and unsupervised learning, model selection, feature engineering, regularization, validation, hyperparameter optimization, and evaluation methodologies • Understanding of modern deep learning methods and architectures, including transformers • Professional experience working with LLMs and understanding transformer architecture, attention, tokenization, context windows, inference, and fine-tuning • Understanding of RAG systems, embeddings, retrieval, and evaluation • Strong Python programming skills and production-quality software engineering practices • Experience with ML frameworks and libraries such as PyTorch, scikit-learn, TensorFlow, or similar • Practical SQL knowledge and experience independently working with large datasets • Practical experience with Docker and containerized development • Strong analytical and critical-thinking skills • Ability to work independently, make sound technical decisions, and take ownership from problem definition through evaluation • Strong communication and collaboration skills across engineering, analytics, and product teams

🏖️ Benefits

• The opportunity to work with a cutting-edge sports platform impacting millions worldwide • Family benefits package • Education - internal and through international conferences and workshops • Top-quality equipment and budget for a mobile phone • Paid package of general physical examination once a year • Sofascore Canteen (lunch options) • Sofascore Bar (coffee and drinks on us) • Numerous other benefits that we would verbally communicate to you