In Customer Care Technology, we build the intelligent applications and infrastructure driving the full customer journey, supporting millions of customers and thousands of customer care specialists. We are seeking a Senior Applied Scientist to join our Berlin-based Applied Science team in a business-critical role. In this position, you will design, build, and scale cutting-edge Agentic AI systems and Large Language Models (LLMs) for high-volume production, directly optimizing customer self-service solutions to handle millions of queries monthly. Working closely with a cross-functional team of data engineers, software engineers, analysts, and product managers, you will turn scientific innovations into scalable AI products that elevate the customer experience.
Learn more about our Applied science team https://jobs.zalando.com/en/what-we-do/applied-science-and-research and how we work together https://jobs.zalando.com/en/where-we-work
INCLUSIVE BY DESIGN
If you think you have what it takes, we encourage you to apply even if you don't meet every single requirement. You may just be the right candidate for this or other roles!
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 throughout the hiring process, please let us know – we are here to assist you.
Discover more about our commitment to creating a diverse and inclusive workplace: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)Drive End-to-End Research: Translate ambiguous, high-impact business challenges in Customer Care Technology into structured research plans, leading projects from discovery to production deployment.
Build Agentic Systems: Apply rigorous scientific methodologies to design, fine-tune, evaluate, and scale advanced LLM applications and agentic workflows.
Own Production Models: Take end-to-end accountability for AI models in production—including architecture design, performance optimization, deployment, and real-time monitoring at scale.
Elevate Standards: Establish best practices for research methodologies, ensuring high-quality, reproducible experiments across the team.
Mentor & Inspire: Coach junior Applied Scientists, fostering a culture of scientific rigor, innovation, and operational excellence.
Collaborate Cross-Functionally: Partner with product managers, data engineers, and software engineers to seamlessly integrate AI solutions into production services.
WE’D LOVE TO MEET YOU IF
AI Productionization: You have a strong track record of autonomously tackling complex research projects and shipping scientific innovations into customer-facing AI products at scale.
Core LLM Expertise: You have extensive expertise in Machine Learning, Deep Learning, and Natural Language Processing (NLP), with a focus on building and scaling production-grade LLM applications.
Agentic System Design: You have a strong understanding of agentic architectures, agent orchestration, hallucination mitigation, and retrieval augmented generation (RAG).
Engineering & Tech Stack: You have excellent programming skills in Python (including frameworks like PyTorch and PydanticAI), strong SQL skills, and hands-on experience with Databricks.
Strategic Communication: You have the ability to think strategically and effectively translate complex technical concepts into clear, actionable insights for non-experts and senior leadership.
Agile & Collaborative Mindset: You have a results-driven, collaborative mindset, feel comfortable navigating high-uncertainty environments, and actively take initiative to uncover high-value research opportunities.
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.
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
Employee shares programme
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 counselling 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
Skills Required
- Proven track record shipping research into production-grade AI products
- Extensive expertise in Machine Learning, Deep Learning, and Natural Language Processing
- Experience building and scaling production-grade Large Language Model applications
- Strong understanding of agentic architectures, agent orchestration, hallucination mitigation, and RAG
- Excellent programming skills in Python (including frameworks like PyTorch and PydanticAI)
- Strong SQL skills
- Hands-on experience with Databricks
- Ability to translate complex technical concepts to non-experts and senior leadership
- Experience mentoring junior applied scientists and fostering scientific rigor
- Comfort working in agile, high-uncertainty environments and driving research from discovery to production
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.








