Machine Learning Engineer (m/f/d)

Description

The company's AI Unit is an established, high-performing team of AI experts that designs, builds and deploys machine learning models for sports betting, trading, media and sports performance products.

You will work with the company's sports datasets, betting transactions, user interaction data and large-scale tracking data. Depending on your interests, you may focus on predictive analytics for sportsbook risk and liquidity-driven odds trading, or on generative AI and deep learning for sports performance modelling, simulation and virtualization.

You will work alongside product owners, technical leads and software engineers to turn research into scalable production systems with measurable business impact across the company's product portfolio.

Responsibilities

• Analyse, explore and visualize large datasets using statistical methods and modern data science tools.
• Build models ranging from predictive and statistical models to deep learning and generative AI.
• Design and implement data processing, training, validation and inference pipelines for production AI systems.
• Test methods, models, algorithms and hypotheses rigorously through historical back-testing, simulations and experiments.
• Move AI solutions into production on the company's AI platform, and monitor, maintain and keep improving them.
• Devise new approaches for analysing sports, betting, tracking and behavioural data to improve products and services.
• Work with product and engineering teams to put model outputs into real product experiences.
• Explain complex technical concepts and findings to technical and non-technical stakeholders.

Requirements

• Strong knowledge of machine learning, statistics and data science.
• Proven software engineering experience with strong Python and Java skills.
• Experience building and deploying production-grade ML solutions.
• Working knowledge of modern ML frameworks such as PyTorch and of large-scale data processing.
• Advanced SQL skills and experience with large datasets.
• Experience in at least one of: predictive modelling, risk management, trading or quantitative analytics; or deep learning, natural language processing, transformers, sequence modelling or representation learning.
• Experience validating models through experiments, simulations and back-testing.
• Experience with cloud computing, preferably AWS.
• Experience with agentic coding tools such as Cursor or Claude Code.
• Bonus: experience with Kafka, Flink, real-time analytics or distributed systems.
• Bonus: experience with tracking, time-series, computer vision, pose estimation or spatiotemporal data.
• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics or a related field.
• Fluent English, written and spoken.
• An autonomous, analytical, creative and collaborative mindset.

Conditions

Engineering offices in Europe, Asia and the US, so you will work with colleagues around the world.

Fully on-site role: you will be in the office five days a week. Exemptions may apply depending on location; your local contact can advise.

Flexible working hours, and autonomy over how you manage your workday and tasks.

Equal-opportunity statement: the company welcomes all applicants.

Benefits

• Social events and team building.
• Vibrant, inclusive community, including Women in Tech and Pride groups open to everyone.
• Global Employee Assistance Programme.
• Access to the Calm and Reulay well-being apps, which support focus, rest, mindfulness and long-term mental resilience.
• Online training videos.