We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.What the role involvesPartner with product and engineering teams to identify and execute machine learning use cases that deliver measurable impact.Design, build, and iterate on machine learning solutions (e.G., classifiers, regressors, ranking/retrieval, and rule-based components).Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring.Implement reliable training and inference pipelines, and help improve reproducibility, testing, and observability.Communicate model behaviour, trade-offs,



and results clearly to both technical and non-technical stakeholders.Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices.What we are looking forBachelor's degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.2+ years of industry experience building and deploying ML systems.Solid proficiency in Python and familiarity with common ML libraries (e.G., PyTorch, XGBoost) and SQL.Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices.Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively.Nice to haveFamiliarity with ML tooling such as MLflow, ZenML, or Metaflow.Hands-on experience with AWS services (e.G.,

📌 Machine Learning Engineer (Madrid)
🏢 Super
📍 Madrid