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Sportradar, the world's leading sports technology company, is seeking a Machine Learning Engineer to join its AI Unit. You will work on designing, developing, and deploying advanced machine learning models that power sports betting, trading, media, and sports performance products. The team leverages Sportradar's unique sports datasets, betting transaction data, user interaction data, and large-scale tracking data to create innovative AI and analytics solutions.
Key responsibilities include:
- Analyzing, exploring, and visualizing large-scale datasets using statistical methods and modern data science tools
- Developing machine learning models ranging from predictive and statistical models to deep learning and generative AI solutions
- Designing and implementing data processing, training, validation, and inference pipelines for production-grade AI systems
- Rigorously validating methods, models, algorithms, and hypotheses through historical back-testing, simulations, and experimentation
- Bringing AI solutions into production using Sportradar's AI platform, with ongoing model monitoring, maintenance, and continuous improvement
- Designing innovative approaches for analyzing sports, betting, tracking, and behavioral data
- Collaborating with product and engineering teams to integrate model outputs into real-world product experiences
- Presenting complex technical concepts and findings to both technical and non-technical stakeholders
The role offers a collaborative environment with colleagues worldwide, flexible working hours, autonomy in managing your workday, and access to well-being resources. The company operates on an office-first model with five days per week on-site in Ljubljana, though certain exemptions may apply depending on location.
REQUIREMENTS:
- 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: predictive modeling, risk management, trading, quantitative analytics, deep learning, Natural Language Processing, transformers, sequence modeling, or representation learning
- Experience validating models through experimentation, simulations, and back-testing
- Experience with cloud computing, preferably AWS
- Experience with agentic coding tools like Cursor or Claude code
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related field
- Fluent in English (written and spoken)
- Autonomous, analytical, creative, and collaborative mindset
BONUS QUALIFICATIONS:
- Experience with Kafka, Flink, real-time analytics, or distributed systems
- Experience with tracking, time-series, computer vision, pose estimation, or spatiotemporal data
