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

THE ROLE & THE TEAM

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.

As 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.

INCLUSIVE BY DESIGN

At 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.

We 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.

do.BETTER - our diversity & inclusion strategy:

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

• Build and optimise ML pipelines for training, deploying, and monitoring AI models.
• Productionize ML models by orchestrating workflows (Apache Airflow) and deploying scalable, reliable solutions on AWS for real-time and batch inference.
• Improve data quality and reliability for real-time and batch inference systems.

WE’D LOVE TO MEET YOU IF

• 2+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks (e.g. PyTorch).
• Proven experience in productionizing ML models and orchestrating ML workflows.
• Experience with PySpark on Databricks (or similar) for scalable data processing and ML model inference.
• You possess excellent communication skills in English and can articulate complex technical topics and solutions clearly and concisely.
• Experience with feature stores, real-time feature engineering or Kubernetes is a plus.

If you think you have what it takes, we encourage you to apply even if you don't meet every single requirement. You may just be the right candidate for this or other roles!

OUR OFFER

● Employee shares program

● 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners

● 2 paid volunteering days a year

● 25 days of vacation a year for full-time employees

● Health and wellbeing options (SportAbo in Zurich)

● Swiss SBB Halbtax (half-fare card)

● Mental health support and coaching available

● Drive your development through our training platform and biannual peer-to-peer review