THE ROLE AND THE TEAM
Our ML Platform team builds the foundational intelligence layer that powers Zalando’s AI-native experiences. We provide the infrastructure to serve low-latency features, embeddings, and real-time updates that enable applied science and product teams to deliver search, recommendations, personalization, forecasting, and emerging GenAI use cases. Today, we operate Zalando’s central Feature Store and are scaling it into a broader discovery hub for customer, product, and content understanding in real time.
As Principal Engineer, you will play a leading role in shaping technical strategy, setting engineering standards, and influencing architecture across ML infrastructure at Zalando. Partnering closely with product leadership, you will co-own the vision and roadmap for the ML Intelligence Platform, ensuring our foundations enable AI-native customer experiences at scale.
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
WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)
ML platform subject matter expertise: Define golden paths and best practices for building real-time features and embedding systems at scale.
Platform reliability: Implement SLOs for feature freshness, data quality, and online/offline consistency; establish monitoring and safe deployment strategies for data/feature pipelines.
Self-service and developer velocity: Champion automation and reusable connectors (batch + streaming), declarative feature definitions, and documentation that accelerates time-to-first-success.
Embedded governance: Build data contracts, lineage, and access controls directly into platform workflows to ensure quality and compliance by default.
Technical leadership: Serve as the senior advisor for ML infra challenges, mentor senior engineers, influence engineering standards, and represent the platform in cross-org discussions.
Strategic partner with product: Work hand-in-hand with product management to define the long-term direction of the ML Intelligence Platform. Influence investment decisions, co-lead roadmap prioritization, and ensure technical architecture and product strategy are tightly aligned.
Grow talent and community: Play a leading role in hiring, onboarding, and mentoring senior engineers, helping to build a strong technical community around ML infrastructure.
WE’D LOVE TO MEET YOU IF YOU HAVE
Proven ML/data platform leadership: 6+ years designing and operating ML infrastructure or large-scale data systems (AWS, EKS, or equivalent).
Feature platform expertise: Strong background in data/feature pipelines, schema evolution, online/offline consistency, or willingness to build deep expertise. Prior experience with feature stores (Hopsworks, Feast, SageMaker) a plus.
Streaming and batch systems: Hands-on experience with Kafka/Nakadi, Flink/Spark, Delta Lake/BigQuery or equivalent.
Distributed systems builder: Comfortable with containers, Kubernetes, and designing scalable, low-latency infra.
Reliability mindset: Skilled in defining/measuring SLOs, monitoring pipelines, and running incident/postmortems with a focus on ML data quality.
Collaboration and communication: Ability to partner with applied scientists, engineers, and products to translate needs into platform capabilities.
BONUS / NICE TO HAVE
Experience with vector databases or embedding serving.
Familiarity with declarative/low-code data transformation frameworks.
Experience with real-time recommendation or personalization systems (as a platform enabler).
Contributions to open source in ML/data infra.
Knowledge of data governance frameworks (GDPR, AI Act, data contracts).
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. Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us
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
Hybrid working model with 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
27 days of vacation a year to start
Relocation assistance available (subject to prior agreement)
Family services, including counselling and support
Health and wellbeing options (including Gympass)
Mental health support and coaching available
