is not just a slogan, it is an attitude. We love technology and we want to excite. We have fun and want to inspire. Our customers and our teams. That’s why we are looking for people who share this spirit. People who are passionate about creating the shopping experience of the future together with 50.000 colleagues across Europe.
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
What's in it for you?
International teams & exciting tasks
30 days vacation & company pension plan
Employees discount & Fitness Collaborations
Training & Education
Open corporate culture & Teamwork
Mobile work (50/50)
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.
Your HR contact
Laura Schröder Phone number:+49 151 27797438
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