EU remote
Machine Learning Engineer (m/f/d)
About this role
ABOUT US: We are looking for a Machine Learning Engineer to join Sportradar's AI Unit, an established, high-performing team of AI experts working on the design, development, and deployment of advanced machine learning models that power sports betting, trading, media, and sports performance products. As part of our AI team, you will leverage Sportradar's unique sports datasets, betting transaction data, user interaction data, and large-scale tracking data to develop innovative AI and analytics solutions.
Depending on your expertise and interests, your work may focus on predictive analytics for sportsbook risk management and liquidity-driven odds trading, or on generative AI and deep learning solutions for sports performance modelling, simulation, and virtualization. You will collaborate closely with product owners, technical leads, and software engineers to transform AI research into scalable production systems that deliver measurable business impact across Sportradar's product portfolio.
THE CHALLENGE: Analyse, explore, and visualize large-scale datasets using statistical methods and modern data science tools. Develop machine learning models ranging from predictive and statistical models to deep learning and generative AI solutions . Design and implement data processing, training, validation , and inference pipelines for production-grade AI systems. Rigorously validate methods, models, algorithms , and hypotheses through historical back-testing, simulations, and experimentation.
Bring AI solutions into production leveraging Sportradar's AI platform, ensuring model monitoring, maintenance, and continuous improvement. Design innovative approaches for analysing sports, betting, tracking, and behavioural data to enhance products and services. Collaborate with product and engineering teams to integrate model outputs into real-world product experiences. Present complex technical concepts and findings to both technical and non-technical stakeholders.
ABOUT YOU: Strong knowledge of machine learning, statistics, and data science . Proven software engineering experience and strong programming skills in Python and Java . Experience building and deploying production-grade ML solutions . Proficiency with modern ML frameworks such as PyTorch and large-scale data processing. Advanced SQL skills and experience working with large datasets . Experience in one or more of the following areas: Predictive modelling, risk management, trading, or quantitative analytics.