Your Tasks

• Design, implementation, and maintenance of end-to-end MLOps pipelines using cloud-native services
• Ownership of the complete ML/AI model lifecycle, including model versioning, performance monitoring, and deployment management
• Collaboration with data scientists to translate experimental work into production-ready solutions
• Close cooperation with cloud and platform teams to ensure security, scalability, and regulatory compliance
• Troubleshooting and resolution of issues across ML pipelines, cloud infrastructure, and the deployment lifecycle
• Strong plus: Ability and willingness to support discussions with less technical stakeholders involved in solution definition and approval (e.g. data privacy or controlling teams)

Your Profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
• Proven professional experience as a Machine Learning Engineer, MLOps Engineer, Data Engineer, or in a similar role
• Professional experience across multiple areas of machine learning, including classical ML, deep learning, and Generative AI
• Experience integrating GenAI / LLMs into scalable, business-critical solutions
• Strong hands-on experience in cloud engineering, preferably on Google Cloud Platform (e.g., Vertex AI)
• Proficiency in Python and SQL, with experience using common ML frameworks such as TensorFlow, PyTorch, and scikit-learn
• Experience deploying and operating ML models in production, covering the full lifecycle from data preparation and feature engineering to model registration, monitoring, and re-training
• Hands-on experience with containerization and orchestration technologies (e.g., Docker, Cloud Run, Kubernetes)
• Knowledge of CI/CD pipelines and infrastructure automation (e.g., Terraform, GitHub Actions)
• Experience working with large-scale data processing systems and applying data engineering best practices (e.g., query optimization, data quality checks, assertions)
• Strong ability to collaborate cross-functionally and actively contribute to both technical and non-technical discussions with diverse stakeholders

About Us

The area Data & AI is the central pillar of our Chief Data Officer organization. We are a cross-functional team consisting of Product Managers, Data and Cloud Engineers and Data Scientists with different specializations ranging from classical ML techniques to GenAI solutions. Within the Value Factory Team, we deliver production-ready, E2E solutions that scale and leverage state of the art insights generation as well as modern technology. As a central hub for Data & AI in the business, we spearhead one of the fastest and most exciting transformations in history: Advancing an iconic brand to Data-&-AI-first player.

The best solutions come from bringing together diverse perspectives. Embracing diversity is key to achieving our vision of becoming the Experience Champion. We value inclusion, foster equal opportunity, and welcome you to be part of our team.