Was du bei uns bewegst: Architect and build scalable recommender systems end-to-end, from feature engineering and modeling to reliable production serving Implement and integrate modern AI and LLM-based capabilities into scalable production systems Write clean, maintainable, and testable production-quality code with a strong focus on reliability and long-term maintainability Take full ownership of ML systems in production, including deployment, monitoring, performance optimisation, and system resilience Enable controlled experimentation and continuous optimisation of recommender systems in production environments Proactively experiment with new approaches, tools, and architectures to continuously improve recommender performance and system design Collaborate closely with data scientists, software engineers, data engineers, and product managers to integrate ML solutions into scalable, production-ready system architectures Continuously improve engineering standards, tooling, experimentation practices, and system robustness Was du mitbringst: Several years of hands‑on experience operating machine learning systems in production at scale Strong software engineering fundamentals, including system design, clean architecture, testing strategies, CI/CD, and code reviews Solid data science foundation in recommender systems Proficiency in
