We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Design & Architecture: Play a key role in the design, architecture, and development of end-to-end data engineering and MLOps solutions with full operational responsibilities on cloud infrastructure (AWS, Databricks, Kubernetes).
• Streaming Pipelines: Gather requirements and design high-throughput, low-latency batch and real-time feature pipelines using Apache Flink (Java) and Spark (Python) to provision production-grade features to our central Hopsworks Feature Store.
• System Operationalization: Drive the operationalization, model serving, and maintenance (MLOps/MLaaS) of our real-time inference sponsored prediction system and new Ad candidate retrieval systems.
• Science Collaboration: Collaborate closely with Applied Scientists to optimize data pipeline runtime, data quality, and model performance, latency, and memory usage.
• Operational Excellence: Take ownership of the operational excellence of our AI systems, implementing robust CI/CD pipelines, continuous monitoring, and automated alerting for distributed systems to maximize scalability and reliability.
• Communication & Roadmapping: Communicate effectively with product managers, data scientists, and engineering peers, translating complex engineering concepts into actionable roadmaps.
• Workflow Automation: Strive to continuously improve and automate the time-to-market for the team's experimentation-to-production workflows.

WE’D LOVE TO MEET YOU IF

• Solid Foundation: You hold a degree in Computer Science, a related technical field, or have equivalent practical experience showcasing strong software engineering fundamentals.
• Streaming & Data Engineering: You have significant hands-on experience designing, building, and maintaining high-throughput, low-latency data streaming applications. Practical experience with Apache Flink and Spark is highly required.
• MLOps & Model Serving: You possess professional experience in machine learning operationalization, model serving (e.g., Triton, SageMaker), data version control, and workflow orchestration (e.g., Airflow or Databricks workflows).
• Strong Programming Skills: You are proficient in Java and/or Python, with a strong passion for writing clean, testable, and maintainable production code. Familiarity with ML libraries (e.g., PyTorch, TensorFlow) is a major plus.
• Modern Practices: You are well-versed in Agile methodologies, CI/CD pipelines, and establishing effective metrics and monitoring for large-scale distributed systems.
• Collaboration & Mentorship: You have experience working closely with applied scientists and mentoring other engineers, with excellent verbal and written communication skills to bridge technical gaps across stakeholders.

OUR OFFER Zalando provides a range of benefits, here’s an overview of what you can expect.

• 27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days)
• 2 paid volunteering days a year
• Hybrid working model with up to 60% remote per week, actual practice is up to each team to best support their collaboration
• Work from abroad for up to 30 working days a year
• Employee shares program
• 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners
• Relocation assistance available (subject to prior agreement)
• Family services, including counseling and support
• Health and wellbeing options (including Wellhub, formerly Gympass)
• Mental health support and coaching available
• Drive your development through our training platform and biannual peer-to-peer review