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: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
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
Skills Required
- 2+ years of experience with PySpark, MLOps, AWS SageMaker, AWS CloudFormation, Apache Airflow, Python, and deep learning frameworks such as PyTorch
- Experience productionizing machine learning models and orchestrating machine learning workflows
- Experience using PySpark on Databricks or a similar platform for scalable data processing and machine learning model inference
- Excellent English communication skills and ability to explain complex technical topics clearly and concisely
- Experience with feature stores, real-time feature engineering, or Kubernetes
Zalando Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zalando and has not been reviewed or approved by Zalando.
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Leave & Time Off Breadth — Paid time off includes a sizable annual allowance that can grow with tenure, plus additional paid days for volunteering. This breadth is highlighted as supportive of work–life balance.
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Wellbeing & Lifestyle Benefits — Mental health support, round‑the‑clock counseling for employees and households, and broad fitness/wellness access are emphasized as robust. Substantial product discounts and partner offers add meaningful lifestyle value.
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Parental & Family Support — Structured support around parental leave—such as buddy programs, re‑onboarding, and paid child sick days—helps ease family responsibilities. Flexible and part‑time leadership options further accommodate parents.
Zalando Insights
What We Do
Welcome to Zalando. Here’s some key info about us: Our position and vision: - We’re Europe’s leading online platform for fashion and lifestyle - Founded in Berlin in 2008, we bring head-to-toe fashion to more than 50 million active customers in 25 markets; offering clothes, footwear, accessories, and beauty - Our vision is to become The Starting Point For Fashion. Our offering: - Our assortment of international brands ranges from world-famous names to local labels - Our platform is a one-stop fashion destination for inspiration, innovation, and interaction - As Europe’s most fashionable tech company, we work hard to find digital solutions for every aspect of the fashion journey: for our customers, partners, and friends of our brand. - Our logistics network with 12 centrally located fulfillment centers allows us to efficiently serve our customers throughout Europe, supported by warehouses in Italy, France, Poland, and Sweden with a focus on local customer needs. Our beliefs: - Our ambition is to combine our passion for self-expression through fashion with our unwavering commitments to sustainability and D&I - We believe that our integration of fashion, operations, and online technology gives us the capability to deliver a compelling value proposition to both our customers and fashion brand partners.
