Senior ML Software Engineer / Lounge by Zalando (all genders)

Stellenbeschreibung:

THE ROLE AND THE TEAM

As a Senior Software / ML Engineer in the Assortment Optimization domain, you'll build the engineering backbone behind machine learning and optimization products that improve one of our most critical levers: buying decisions. Your work will help determine what we buy, how much we buy, and how we holistically optimize Lounge's assortment, with direct impact on key long-term business outcomes.

This is a highly engineering-driven role: the solutions you build must be scalable enough to handle a large volume of inbound articles and be reliable by design, because they influence some of the most important commercial decisions in Lounge. You'll focus on production-grade systems with robust pipelines, strong observability, and operational excellence.

Algorithmic-driven buying in Lounge is still a green field: new decision products to invent, foundational capabilities to build, and a direct opportunity to shape the direction of the domain while delivering outsized impact early.

You'll work closely with Applied Scientists, Software Engineers, Product, and commercial stakeholders to deliver decision-support solutions that are actionable, explainable, well evaluated, and production-ready.

INCLUSIVE BY DESIGN

At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds.

We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.

We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you during the hiring process, please let us know – we are here to assist you.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

  • Build and operate production-grade ML/optimization systems that support buying decisions (e.g., quantity recommendations, assortment selection, budget allocation).
  • Develop scalable and performant data and ML pipelines (batch and/or near-real-time where needed), ensuring reliability, observability, and cost-efficiency.
  • Own operational excellence: CI/CD, testing strategies, code quality, reproducibility, monitoring, alerting, and incident-friendly runbooks.
  • Enable fast experimentation for Applied Scientists by providing robust tooling and clean interfaces for training, evaluation, and deployment.
  • Partner end-to-end with scientists and stakeholders to translate business constraints into reliable software components integrated into daily buying workflows.
  • Build dashboards and operational visibility so teams can trust, understand, and continuously improve decision systems in production.

REQUIREMENTS

  • You have 3+ years of experience building and running data/ML systems in production (ML platform, MLOps, data engineering, or ML-heavy backend).
  • You write production-quality Python (clean architecture, tests) and follow software delivery best practices (code reviews, CI/CD).
  • You are strong in software engineering fundamentals: reliability, scalability, observability, and maintainable system design.
  • You have hands-on experience with modern data/ML tooling such as Databricks/Spark, MLflow, Airflow/DBT, feature pipelines, or similar.
  • You are comfortable with cloud and infrastructure concepts (e.g., AWS, Kubernetes, containers).
  • You communicate clearly with both technical and non-technical stakeholders and enjoy turning ambiguous problems into dependable systems.

WHY THIS ROLE

Your systems will power core buying decisions with high visibility and measurable commercial outcomes. You’ll have end-to-end ownership from enabling experimentation to production deployment and monitoring. You’ll collaborate in a strong cross-functional environment with Applied Scientists and Engineers to build scalable tools that support decision making in a domain with plenty of room to innovate.

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

ABOUT LOUNGE BY ZALANDO

Lounge by Zalando is an online outlet for fashion and lifestyle products in 20+ European countries. We offer our members daily, time-limited sale campaigns with discounts of up to 75% off the recommended retail price. However, Lounge by Zalando is so much more than discounts. Our strength lies in our focus on fashion and lifestyle brands: from sought-after labels to niche brands, from famous international names to trendy luxury brands, we make sure to meet the fashion taste of all our customers, who are always on the hunt for the best products at the best prices. Working with our brand partners, we're pioneering innovative supply-chain and production processes and offer them an impactful and smart solution, creating a new way to shop for fashion - and a new way to sell it.

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NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    03 Apr 2026
  • Standort:

    WorkFromHome

    Einsatzort:

    Berlin, Germany
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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