Machine Learning / Data Engineer - Reco & Lifestyle Intelligence (All Genders)

pbTHE ROLE THE TEAM /b The Reco Lifestyle Intelligence team is at the forefront of realizing Zalando’s AI ambition, We build the customer and assortment understanding that lets Zalando reason about why a product fits a given customer, and translate that understanding into discovery experiences that go beyond similarity-based recommendation. The team builds core, foundational capabilities like customer and assortment intelligence powered by advanced embeddings, sequential modeling, and outfit intelligence. In parallel, the team builds interactive UX components delivering tailored product suggestions across our customer journeys, where the foundational capabilities could be integrated with. /ppAs a Machine Learning / Data Engineer in Recommendations Lifestyle Intelligence, you will design, deploy, and scale end-to-end ML and GenAI systems powered by 100+ data pipelines for 60+ million Zalando customers. Collaborating closely with Applied Scientists, Product Managers, and Data Engineers, you will translate cutting-edge models into high-throughput, low-latency production microservices. You will take ownership of the full ML lifecycle - from feature engineering and offline training to online inference, continuous monitoring, and MLOps infrastructure. /ppbINCLUSIVE BY DESIGN /b /ppAt Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses. We only want to know why you’re great for this role, so please avoid including your picture, age, and marital status in your CV as well. /ppWe want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process. /ppbWHAT WE’D LOVE YOU TO DO (AND LOVE DOING) /b /pulliBuild and optimise ML pipelines for training, deploying, and monitoring AI models. /liliProductionize ML models by orchestrating workflows (Apache Airflow) and deploying scalable, reliable solutions on AWS for real-time and batch inference. /liliImprove data quality and reliability for real-time and batch inference systems. /lili2+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks (e.g. PyTorch). /liliProven experience in productionizing ML models and orchestrating ML workflows. /liliExperience with PySpark on Databricks (or similar) for scalable data processing and ML model inference. /liliYou possess excellent communication skills in English and can articulate complex technical topics and solutions clearly and concisely. /liliExperience with feature stores, real-time feature engineering or Kubernetes is a plus. /li /ulh3OUR OFFER /h3ulliEmployee shares program /lili40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners /lili2 paid volunteering days a year /lili25 days of vacation a year for full-time employees /liliHealth and wellbeing options (SportAbo in Zurich) /liliSwiss SBB Halbtax (half-fare card) /liliMental health support and coaching available /liliDrive your development through our training platform and biannual peer-to-peer review /li /ul #J-18808-Ljbffr