ML & Data Engineer — Recommender & Lifestyle Intelligence

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

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.