Machine Learning Engineer — Injury Risk

Role overview Develop machine learning models that help identify injury risk and support return-to-play decisions in professional sport. The work combines time-series and clinical language data, model ownership, and close collaboration with team doctors.

Responsibilities - Build and maintain models for injury risk and return-to-play (RTP) decisions. - Work with time-series data and clinical text as part of the modelling process. - Collaborate directly with team doctors on the clinical use of the models. - Take product ownership of model work from development through integration.

Requirements - Experience developing machine learning models, including with PyTorch. - Ability to work with time-series data. - Familiarity with clinical natural language processing. - Interest in applying machine learning to athlete health and clinical decisions.

Benefits and work setup - Full-time role based in Berlin or remote within the EU, with quarterly in-person gatherings. - Meaningful equity and product ownership from the start. - €2,000 annual budget for learning, including courses, conferences, and clinical certifications.