Job
- Level
- Senior
- Job Field
- Data, Back End
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Berlin
- Working Model
- Onsite
Job Summary
In this role, you will develop scalable ML infrastructure and optimize online serving services using Kubernetes while also driving automation and security of platform operations.
Job Technologies
Your role in the team
- Our ML Platform team builds the core ML platform capabilities powering Zalando's AI-native experiences. We provide low-latency features, embeddings, real-time inference infrastructure, and scalable ML platform capabilities 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 evolving the next generation of Kubernetes-native AI runtime infrastructure, enabling scalable online serving, distributed GPU workloads, and self-service ML platform operations across the company.
- As a Senior Software Engineer (ML Platform), you will play a key role in designing, building, and scaling these core ML infrastructure services. You'll work hands-on with distributed systems, streaming pipelines, Kubernetes-native serving infrastructure, and platform automation, while also mentoring peers and contributing to engineering best practices across the team.
- Own the design and implementation of scalable real-time feature platforms, online serving infrastructure, and distributed ML runtime systems. Bring strong technical judgment to ensure our platform foundations are reliable, reusable, and operationally mature.
- Deliver and maintain SLOs for feature freshness, data quality, online/offline consistency, and runtime reliability; implement monitoring, observability, and safe deployment practices.
- Drive automation and self-service (IaC, GitOps, CI/CD), reusable deployment templates, and operational tooling that reduce friction and accelerate time-to-first-success for applied scientists and engineers.
- Contribute to reusable platform integrations and deployment automation that improve how ML systems interact with developer tooling and internal AI platform capabilities.
- Implement identity and access management, secrets management, network isolation, and data governance built in from the start to ensure compliance and trustworthiness by default.
- Act as a key technical contributor for complex ML infrastructure challenges, mentor junior colleagues, and raise the engineering bar through reviews, pairing, and knowledge sharing.
- Übernehmen Sie die Verantwortung für technische Designentscheidungen innerhalb des Teams und bringen Sie fundierte Beiträge zu langfristigen Plattform- und Runtime-Infrastruktur-Strategien in Abstimmung mit Produkt- und Senior-Engineering-Führungskräften.
- Play an active role in hiring, onboarding, and mentoring engineers, helping to build a strong technical culture around ML infrastructure and platform engineering.
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Our expectations of you
Qualifications
- You have a background in building or integrating developer tooling, platform automation, or workflow systems, including emerging AI-assisted development or agentic workflows.
- You have a track record of building reliable systems with SLOs, monitoring, and deployment safeguards, and are comfortable handling incident response and capacity planning.
- You have strong collaboration and communication skills, enabling you to work effectively with engineers, applied scientists, and product partners to translate requirements into reliable platform capabilities.
Experience
- You have 5+ years of experience building and operating ML Infrastructure or large-scale distributed systems on a cloud platform (AWS/EKS or equivalent), with strong skills in containerization (Docker), Kubernetes, and streaming/batch processing (e.g., Kafka/Kinesis, Spark/Flink).
- You have hands-on experience with data/feature engineering pipelines, schema evolution, and ensuring online/offline consistency, with familiarity with feature stores (e.g., Feast, SageMaker).
- You are experienced in designing and operating low-latency, high-scale distributed systems that meet strict throughput targets, including caching, request shaping, and traffic management.
- You have experience operationalizing Kubernetes-native ML workloads (e.g., model serving, deployment, runtime) using technologies like NVIDIA Triton, MLflow, Kubeflow, or ZenML.
- You are proficient in security and governance (e.g., IAM, secrets management, network boundaries) and have experience embedding compliance into engineering workflows.
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What we 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 program.
- 40% Rabatt auf Mode- und Schönheitsprodukte, die von Zalando verkauft und versendet werden, 30% Rabatt auf Lounge by Zalando, Rabatte von externen Partnern.
- 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.
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Benefits
Work-Life-Integration
Food & Drink
Health, Fitness & Fun
Topics that you deal with on the job
Job Locations
This is your employer
Zalando SE
Zalando is the leading online fashion platform in Europe, connecting customers, brands, and partners in 17 markets. We offer the latest styles and trends from the best fashion brands around the world, all in one place. With Zalando, you can find the perfect outfit for any occasion, whether you're looking for casual wear, formal wear, or something in between. We also offer a wide range of sizes and styles to suit every customer's needs. Shop with us today and see why we're the leading fashion destination in Europe.
Description
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Trade
Employer reviews
by devworkplaces.com
Total
(1 Review)3.4
Culture
3.5Workingconditions
4.4Engineering
3.1Career Growth
2.6
Senior Software Engineer
- Location
- Berlin
- Working Model
- Onsite
- Diversity
- Open for all genders
- English Only
- English only required
