Senior ML Ops Engineer

KAYAK, part of Booking Holdings, is seeking a Senior MLOps Engineer to design and implement the machine learning infrastructure and production lifecycle. This role bridges data science and production engineering, building scalable pipelines for model training, deployment, and monitoring. You will join the Machine Learning Platform team and work closely with Data Scientists and Operations to ensure ML models are reliable, reproducible, and performant at scale. This hybrid position requires commuting to the Berlin office three times a week.

• Build and maintain end-to-end ML infrastructure, including CI/CD pipelines, model orchestration, and automated training pipelines.
• Own model deployment and serving, defining standards and tooling for low-latency, high-availability ML services.
• Develop core MLOps capabilities such as feature stores, model registries, and automated monitoring for performance and data drift.
• Operationalize Kubernetes autoscaling and GPU provisioning, enabling self-service infrastructure for ML practitioners.
• Improve platform reliability and performance through observability, SLOs, and automation.
• Empower Data Scientists with standardized 'golden path' workflows.

• Experience building and operating ML platforms in production environments.
• Solid working knowledge of containerization and orchestration (Docker, Kubernetes), Linux internals, and model serving at scale.