Senior Machine Learning Engineer (all genders)

Zalando GmbH; Berlin; Vor Ort; EUR 65.000 - 90.000; Vollzeit

Benefits dieser Stelle

27 days of holiday

2 paid volunteering days

Hybrid working model

Employee shares program

40% off fashion products

Health and wellbeing options

Mental health support

Zusammenfassung

Zalando GmbH is looking for a Senior ML/Data Engineer in Berlin. In this role, you will collaborate with cross-functional teams to design and develop robust data engineering and machine learning solutions. This is an opportunity to work with cutting-edge technologies in a hybrid environment.

The position requires a strong foundation in software engineering, hands-on experience in data streaming applications, and proficiency in Java or Python. Attractive employee benefits and opportunities for professional development are also offered.

Qualifikationen

• Degree in Computer Science or relevant field, or equivalent experience.
• Significant hands-on experience with data streaming applications including Apache Flink and Spark.
• Experience in machine learning operationalization and model serving.
• Proficient in Java and/or Python with a focus on maintainable code.
• Familiar with Agile methodologies and CI/CD practices.

Aufgaben

• Design and develop end-to-end data engineering and MLOps solutions.
• Gather requirements for high-throughput, low-latency pipelines using Apache Flink and Spark.
• Drive operationalization and maintenance of AI systems.
• Collaborate with scientists to optimize data pipelines.
• Implement CI/CD pipelines and monitor distributed systems.
• Improve and automate workflows for experimentation to production.

Kenntnisse

Data streaming applications

Apache Flink

Apache Spark

MLOps

Java

Python

CI/CD pipelines

Agile methodologies

Ausbildung

Degree in Computer Science or related field

Tools

AWS

Databricks

Kubernetes

Jobbeschreibung

THE ROLE & THE TEAM

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

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.
• Workflow Automation: Continuously improve and automate the time‑to‑market for the team's experimentation‑to‑production workflows.

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. Practical experience with Apache Flink and Spark is highly required.
• 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.
• Modern Practices: You are well‑versed in Agile methodologies, CI/CD pipelines, and establishing effective metrics and monitoring for large‑scale distributed systems.
• 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.

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