(Senior) MLOps Engineer – Data Science | (Senior) MLOps Engineer (m/w/d) – Data Science

Job Summary

This role involves developing, operating, and continuously evaluating Machine Learning (ML) models and infrastructure within a high-scale logistics system environment. The MLOps Engineer will collaborate closely with software engineering teams to ensure a robust and scalable ML infrastructure, focusing on real-time, high-precision data-driven decision-making for areas like tour planning, capacity control, and warehouse operations efficiency. Key responsibilities include building ETL pipelines for event-based data systems, preparing data for model training and analysis, and presenting insights via dashboards. The ideal candidate must possess strong MLOps understanding, experience with Kubernetes, Docker, CI/CD, and Azure, coupled with solid Python data toolkit skills (Pandas, XGBoost, Scikit-learn). This position requires excellent communication skills to articulate technical topics to non-technical stakeholders in logistics and operations, making a tangible impact on the business.