Senior Machine Learning Engineer (all genders)

Role Senior ML/Data Engineer – Join Zalando Marketing Services (ZMS) Tech to design and build data pipelines and machine learning infrastructure for real‑time ad‑tech platforms. Responsibilities - Design and architect end‑to‑end data engineering and MLOps solutions on AWS, Databricks, Kubernetes. - Build high‑throughput, low‑latency streaming and batch feature pipelines using Apache Flink (Java) and Spark (Python) for the Hopsworks Feature Store. - Operationalize and serve machine‑learning models (MLOps/MLaaS) for real‑time sponsored prediction and ad candidate retrieval systems. - Collaborate with Applied Scientists to optimise data quality, pipeline runtime, model performance, latency and memory usage. - Ensure operational excellence through CI/CD pipelines, monitoring, alerting and scalability of distributed AI systems. - Communicate roadmaps and translate technical concepts for product managers, data scientists and engineering peers. - Automate experimentation‑to‑production workflows to improve time‑to‑market. Qualifications - Degree in Computer Science or related field, or equivalent practical experience. - Significant experience designing, building and maintaining high‑throughput, low‑latency streaming applications; strong hands‑on with Apache Flink and Spark. - Professional experience in MLOps and model serving (e.g., Triton, SageMaker), data version control and workflow orchestration (Airflow, Databricks). - Proficient in Java and/or Python; familiarity with ML libraries such as PyTorch or TensorFlow. - Strong grasp of Agile methodologies, CI/CD, and metrics/monitoring for large‑scale distributed systems. - Excellent communication skills and experience mentoring engineers and collaborating with applied scientists. What We Offer - 27 days of holiday (increasing up to 30 days), plus 2 paid volunteering days. - Hybrid working model with up to 60 % remote and up to 30 days per year working from abroad. - Employee share program and 40 % discount on Zalando fashion and beauty products. - Relocation assistance, family services, health and wellbeing options, mental‑health support and coaching. - Continuous development through training platforms and bi‑annual peer‑to‑peer reviews.