Senior Machine Learning Engineer (all genders)

Das ist der Job

Practical experience with Apache Flink and Spark is highly required.

Darum lohnt es sich

THE ROLE & THE TEAM Zalando Marketing Services (ZMS) stands for a new era of marketing in fashion e-commerce.

As a Senior ML/Data Engineer, you will work with a cross‑functional team of Applied Scientists, Software Engineers, Data Engineers, Product Managers, and Designers to build and scale data pipelines and machine learning infrastructure for our next‑generation AdTech platform.

Workflow Automation: Continuously improve and automate the time‑to‑market for the team's experimentation‑to‑production workflows. Modern Practices: You are well‑versed in Agile methodologies, CI/CD pipelines, and establishing effective metrics and monitoring for large‑scale distributed systems.

OUR OFFER 27 days of holiday a year to start for full‑time employees (+1 day for every calendar year up to 30 days) 2 paid volunteering days a year Hybrid working model with up to 60% remote per week, actual practice is up to each team to best support their collaboration Work from abroad for up to 30 working days a year Employee shares program 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners Relocation assistance available (subject to prior agreement) Family services, including counseling and support Health and wellbeing options (including Wellhub, formerly Gympass) Mental health support and coaching available Drive your development through our training platform and biannual peer‑to‑peer review #J-18808-Ljbffr We enable fashion, beauty, and lifestyle partners to engage with over 60 million active customers across European markets on Zalando and beyond, providing access to exclusive audiences and smart marketing tools.

In ZMS Tech, we are evolving our real‑time inference sponsored prediction system and building a brand‑new Ad candidate retrieval system to handle millions of sponsored ads opportunities in a real‑time, low‑latency, high‑volume fashion environment.

INCLUSIVE BY DESIGN We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING) Design & Architecture: Play a key role in the design, architecture, and development of end‑to‑end data engineering and MLOps solutions with full operational responsibilities on cloud infrastructure (AWS, Databricks, Kubernetes).

Streaming Pipelines: Gather requirements and design high‑throughput, low‑latency batch and real‑time feature pipelines using Apache Flink and Spark to provision production‑grade features to our central Hopsworks Feature Store.

System Operationalization: Drive the operationalization, model serving, and maintenance of our real‑time inference sponsored prediction system and new Ad candidate retrieval systems. Science Collaboration: Collaborate closely with Applied Scientists to optimize data pipeline runtime, data quality, and model performance, latency, and memory usage.

Operational Excellence: Take ownership of the operational excellence of our AI systems, implementing robust CI/CD pipelines, continuous monitoring, and automated alerting for distributed systems to maximize scalability and reliability.

Communication & Roadmapping: Communicate effectively with product managers, data scientists, and engineering peers, translating complex engineering concepts into actionable roadmaps.

WE’D LOVE TO MEET YOU IF Solid Foundation: You hold a degree in Computer Science, a related technical field, or have equivalent practical experience showcasing strong software engineering fundamentals.

Streaming & Data Engineering: You have significant hands‑on experience designing, building, and maintaining high‑throughput, low‑latency data streaming applications.

MLOps & Model Serving: You possess professional experience in machine learning operationalization, model serving (e.g., Triton, SageMaker), data version control, and workflow orchestration (e.g., Airflow or Databricks workflows).

Strong Programming Skills: You are proficient in Java and/or Python, with a strong passion for writing clean, testable, and maintainable production code. Familiarity with ML libraries (e.g., PyTorch, TensorFlow) is a major plus.

Collaboration & Mentorship: You have experience working closely with applied scientists and mentoring other engineers, with excellent verbal and written communication skills to bridge technical gaps across stakeholders.