machine learning engineer

Super is a global technology group building a platform for sports, gaming, and fan-centric experiences. The organization develops technology to power immersive, responsible, and personalized entertainment for millions of customers across international markets.

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives;
• Design and develop scalable machine learning models, including classifiers, regressors, and rule-based systems;
• Own the full ML lifecycle from data exploration and feature engineering to model training, evaluation, and deployment;
• Translate complex technical concepts into clear insights for technical and non-technical stakeholders;
• Set and guide technical direction across ML projects to ensure alignment with best practices and business goals;
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

• Master's degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field;
• 7+ Years of industry experience building and deploying ML models at scale;
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy;
• Proficiency in Python with libraries such as PyTorch, XGBoost, and Scikit-learn;
• Strong SQL skills;
• Experience with machine learning pipelines and orchestration tools like Airflow or SageMaker Pipelines;
• Deep understanding of machine learning fundamentals, including Large Language Models (LLMs);
• Track record of shipping production-level ML products and maintaining high code quality;
• Excellent problem-solving skills with the ability to scope complex ML projects;
• Nice to have: Familiarity with ML tooling such as MLflow, ZenML, or Metaflow, hands-on experience with AWS services, exposure to streaming data platforms such as Kafka, contributions to open-source ML projects or publications in ML conferences.

• Medical / Health Insurance;
• Open Annual Leave;
• Employee Assistance Programme;
• Training & Learning Development;
• Additional benefits vary by country.