Senior Software Engineer (all genders)

Role Our ML Platform team builds core machine‑learning platform capabilities that power Zalando’s AI‑native experiences, including low‑latency feature serving, embeddings, real‑time inference, and a central Feature Store. As a Senior Software Engineer (ML Platform) you will design, build, and scale these infrastructure services, working with distributed systems, streaming pipelines, Kubernetes‑native serving, and platform automation while mentoring peers. Responsibilities - Own design and implementation of scalable real‑time feature platforms, online serving infrastructure, and distributed ML runtime systems. - 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 to accelerate time‑to‑first‑success for applied scientists and engineers. - Contribute to reusable platform integrations and deployment automation that improve ML system interactions 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. - 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. - Take ownership of technical design decisions and contribute to long‑term platform and runtime infrastructure strategy with product and senior engineering leadership. - Participate in hiring, onboarding, and mentoring engineers to build a strong technical culture around ML infrastructure and platform engineering. Qualifications - 5+ years of experience building and operating ML infrastructure or large‑scale distributed systems on a cloud platform (AWS/EKS or equivalent), with strong containerization (Docker) and Kubernetes skills. - Hands‑on experience with streaming/batch processing (e.g., Kafka/Kinesis, Spark/Flink) and data/feature engineering pipelines, schema evolution, and online/offline consistency; familiarity with feature stores such as Feast or SageMaker. - Experience designing and operating low‑latency, high‑scale distributed systems, including caching, request shaping, and traffic management. - Proven ability to operationalize Kubernetes‑native ML workloads (model serving, deployment, runtime) using technologies like NVIDIA Triton, MLflow, Kubeflow, or ZenML. - Background in building or integrating developer tooling, platform automation, or workflow systems, including emerging AI‑assisted development. - Track record of building reliable systems with SLOs, monitoring, and deployment safeguards; comfortable with incident response and capacity planning. - Proficiency in security and governance (IAM, secrets management, network boundaries) and embedding compliance into engineering workflows. - Strong collaboration and communication skills to work effectively with engineers, applied scientists, and product partners. What We Offer - 27 days of holiday per year (increasing up to 30 days with tenure) plus 2 paid volunteering days. - Employee shares program and 40 % discount on Zalando fashion and beauty products (30 % discount on Zalando Lounge). - Relocation assistance (subject to prior agreement). - Family services, health and wellbeing options, mental health support and coaching. - Opportunities for development through training platforms and bi‑annual peer‑to‑peer reviews.