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

Zalando GmbH; Zürich; Vor Ort; CHF 150.000 - 190.000; Vollzeit

Benefits dieser Stelle

Employee shares program

40% off fashion and beauty products

2 paid volunteering days a year

25 days vacation a year

Health and wellbeing options

Swiss SBB Halbtax

Mental health support

Training platform and peer reviews

Zusammenfassung

Zalando in Zürich is seeking a Machine Learning / Data Engineer for Recommendations & Lifestyle Intelligence. You will design, deploy, and scale end-to-end ML and GenAI systems powering pipelines for 60+ million customers, translating models into high-throughput microservices.

Collaborate with Applied Scientists, Product Managers, and Data Engineers; own the full ML lifecycle from feature engineering to online inference and monitoring, with a focus on low latency and robust MLOps.

Qualifikationen

• 2+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks.
• Proven productionization of ML models and orchestration of ML workflows.
• Experience with PySpark on Databricks (or similar) for scalable data processing and ML model inference.
• Excellent English communication skills to articulate complex topics clearly.
• Experience with feature stores or real-time feature engineering; Kubernetes is a plus.

Aufgaben

• Build and optimise ML pipelines for training and deployment.
• Productionize models and deploy scalable ML solutions on AWS for real-time and batch inference.
• Improve data quality and reliability for real-time and batch inference systems.
• Collaborate with Applied Scientists, Product Managers, and Data Engineers to productionize models and ML workflows.
• Design end-to-end ML systems and maintain low-latency production microservices.

Kenntnisse

PySpark

ML Ops

AWS SageMaker

Airflow

Python

PyTorch

Databricks

Kubernetes

English communication

Feature stores

Tools

Databricks

Kubernetes

Airflow

Jobbeschreibung

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.

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.
• 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.

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