ML/MLOps Engineer

Your responsibilities, Partner with Data Science teams to productionize models and work across the ML lifecycle – from experimentation and training to deployment, monitoring, and continuous improvement, Design and implement scalable ML infrastructure, with the opportunity to take ownership of architecture and deployment decisions, Build and maintain CI/CD pipelines for model development, testing, and deployment on Databricks or AWS SageMaker, Establish MLOps best practices: experiment tracking, model versioning, feature stores, and governance (MLflow, Unity Catalog, or SageMaker ecosystem), Monitor and optimize ML infrastructure for performance, cost efficiency, and reliability, Work on real-world ML systems running in production – not just experimental models What we offer, Non-corporate work environment among experienced engineers, Individual growth & development plan supported by cyclical feedback sessions, Access to knowledge platforms (e.g. Pluralsight), Equipment of your choice, Financing of conferences, external trainings, and certifications, Language lessons (English, German and Polish for foreigners), LuxMed private medical care, Weekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledge, Employee referral program, Rewards for the success of the month and year awarded by our employees, Special rewards for your years with us (G-Man), Integration activities