THE ROLE & THE TEAM
We are looking for a Senior Machine Learning Engineer to enhance Zalando’s recommendation ML systems, making them more scalable, efficient, and impactful. You will play a key role in productionizing ML models, optimising pipelines, and ensuring seamless deployment of high-performing recommendation systems. Working closely with Applied Scientists, Product and Software Engineers, you will help shape the future of personalized shopping experiences for millions of customers.
WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)
Build and optimise ML pipelines for training, deploying, and monitoring recommendation models.
Productionize ML models by orchestrating workflows (Apache Airflow) and deploying scalable, reliable solutions on AWS for real-time and batch inference.
Improve data quality and reliability for real-time and batch inference systems.
WE’D LOVE TO MEET YOU IF…
5+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks (e.g. PyTorch).
Proven experience in productionizing ML models and orchestrating ML workflows.
Experience with PySpark on Databricks (or similar) for scalable data processing and ML model inference.
Strong collaboration and communication skills.
Experience with feature stores, real-time feature engineering or Kubernetes is a plus.
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 Zalando Lounge, discounts from external partners
2 paid volunteering days a year
27 days of vacation a year to start
Relocation assistance available (subject to prior agreement)
Family services, including counseling and support
Health and wellbeing options (including Gympass)
Mental health support and coaching available
Drive your development through our training platform and biannual peer-to-peer review
Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us
INCLUSIVE BY DESIGN
At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.
We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.
do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy
Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups
Opportunity to work from abroad for 30 (working) days per calendar year
ABOUT ZALANDO
It’s the perfect time to join Zalando on our journey, from being a pioneer in the world of e-commerce, to the starting point for fashion in Europe. We connect customers, brands, and partners across 23 markets.
Help us drive digital and sustainable solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 48 million active customers through a team of diverse skill-sets, cultural backgrounds, and interests.
Our values https //jobs.zalando.com/en/our-founding-mindset
do.More - our sustainability strategy https //corporate.zalando.com/en/sustainability
Follow us on Instagram instagram.com/insidezalando
Please note that all applications must be completed using the online form - we do not accept applications via email.
Skills Required
- 5+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks (e.g., PyTorch).
- Proven experience in productionizing ML models and orchestrating ML workflows.
- Experience with PySpark on Databricks or similar for scalable data processing and ML model inference.
- Build and optimize ML pipelines for training, deploying, and monitoring recommendation models and improve data quality for real-time and batch inference.
- Strong collaboration and communication skills.
- Experience with feature stores, real-time feature engineering, or Kubernetes.
Zalando Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zalando and has not been reviewed or approved by Zalando.
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Leave & Time Off Breadth — Paid time off includes a sizable annual allowance that can grow with tenure, plus additional paid days for volunteering. This breadth is highlighted as supportive of work–life balance.
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Wellbeing & Lifestyle Benefits — Mental health support, round‑the‑clock counseling for employees and households, and broad fitness/wellness access are emphasized as robust. Substantial product discounts and partner offers add meaningful lifestyle value.
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Parental & Family Support — Structured support around parental leave—such as buddy programs, re‑onboarding, and paid child sick days—helps ease family responsibilities. Flexible and part‑time leadership options further accommodate parents.
Zalando Insights
What We Do
Welcome to Zalando. Here’s some key info about us: Our position and vision: - We’re Europe’s leading online platform for fashion and lifestyle - Founded in Berlin in 2008, we bring head-to-toe fashion to more than 50 million active customers in 25 markets; offering clothes, footwear, accessories, and beauty - Our vision is to become The Starting Point For Fashion. Our offering: - Our assortment of international brands ranges from world-famous names to local labels - Our platform is a one-stop fashion destination for inspiration, innovation, and interaction - As Europe’s most fashionable tech company, we work hard to find digital solutions for every aspect of the fashion journey: for our customers, partners, and friends of our brand. - Our logistics network with 12 centrally located fulfillment centers allows us to efficiently serve our customers throughout Europe, supported by warehouses in Italy, France, Poland, and Sweden with a focus on local customer needs. Our beliefs: - Our ambition is to combine our passion for self-expression through fashion with our unwavering commitments to sustainability and D&I - We believe that our integration of fashion, operations, and online technology gives us the capability to deliver a compelling value proposition to both our customers and fashion brand partners.
