ZS

Senior Software Engineer - Machine Learning (all genders)

Zalando SE•Technology
BerlinFull-timeOn sitelast week

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The Lounge Assortment Optimisation team builds the decision products behind a better assortment and customer experience. Our portfolio combines:

Optimisation systems that improve how the assortment is planned and operated;
Forecasting products that estimate demand, sell-through, and commercial outcomes; and
Generative AI solutions that improve product curation, content creation, and operational workflows.

As a Senior Software Engineer (Machine Learning), you will make these products reliable in production.

You will build the data, software, deployment, and monitoring foundations that allow models to move safely from experimentation into daily commercial use.

This is an engineering role at the intersection of data platforms, machine learning, optimisation, and product development.

You will work closely with Applied Scientists, Product Managers, Engineers, and commercial stakeholders to turn ambiguous problems into trusted, scalable systems.

📌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.

do.BETTER - our diversity & inclusion strategy: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion

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

Build and operate production systems for optimisation, forecasting, machine learning, and Generative AI use cases.
Design scalable data and ML pipelines using Python, Databricks, Spark, Airflow, and dbt, with clear data contracts and reliable failure handling.
Enable Applied scientists to develop and evaluate models efficiently by providing reusable training, evaluation, deployment, and experiment-tracking capabilities.
Productionise models: define dependable inputs and outputs, automate deployment, monitor quality and performance, and make model behaviour traceable in production.
Develop and operate workloads in the appropriate execution environment: Databricks jobs for distributed data and ML processing, and Dockerised applications running as Kubernetes pods where that runtime is needed.
Build operational dashboards, alerts, and runbooks so that users and engineers can understand system state, identify issues, and respond effectively.
Work with product and commercial partners to convert business rules and decision requirements into maintainable software components.
Raise the engineering bar through pragmatic standards for system design, testing, code review, CI/CD, observability, and operational ownership.

📌WE’D LOVE TO MEET YOU IF

You have 3+ years of experience building and running data or ML systems in production, for example in MLOps, data engineering, ML platforms, or ML product development.
You write maintainable production Python and follow established software-delivery practices, including automated testing, code review, and CI/CD.
You're strong in software engineering fundamentals: reliability, scalability, observability, and maintainable system design.
You understand how cloud workloads are deployed and run, including AWS, Docker containers, and Kubernetes-based execution.
You communicate clearly with both technical and non-technical stakeholders and enjoy turning ambiguous problems into dependable systems.
Experience with Generative AI products, including LLM evaluation and monitoring, is a plus. Familiarity with AI-assisted development tools such as Codex or Claude Code or Co-pilot is welcome.

📌OUR OFFER

Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we 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
27 days of vacation a year to start for full-time employees
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.

https://www.zalando-lounge.de

Job overview

Posted
20 October 2026
Location
Berlin
Employment type
Full-time
Work model
On site

Company

ZS

Zalando SE

Berlin
Stated on the employer’s website

Gebetsräume auf dem Berliner Campus, laut D&I-Report 2022 gemeinsam mit dem Muslim Community Network der Beschäftigten aufgewertet; die Berlin-Seite der Karriereseite nennt „Gebetsräume“ unter den Campus-Features — standortgebunden, nur Stellen mit Ort Berlin (Logistikzentren ohne Beleg)

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