Senior MLOps Engineer (m/f/d)

Introduction

You take AI models from prototype all the way to safe production use, even under power and air-gap conditions.

Tasks

• You design and are responsible for end-to-end ML pipelines as well as CI/CD and model release processes.
• You manage containerization, deployment strategies, and hybrid cloud and on-premise orchestration of models.
• You define and implement monitoring, drift detection, A/B testing, and operational KPIs for model performance and reliability.
• You drive reproducibility as well as metadata and experiment tracking at scale and ensure secure and compliant deployments.
• You mentor MLOps and engineering colleagues, conduct architecture reviews, and coordinate cross-team production rollouts.
• You optimize models and runtime environments for isolated and energy-efficient deployment environments.

Placeholder Job Ad Video (do not remove)

Qualifications

• You bring several years of experience in MLOps or production ML engineering with end-to-end delivery responsibility.
• You have solid practical experience in containerization, Kubernetes/OpenShift, cloud platforms (Azure/AWS/GCP), as well as GitOps and CI/CD practices.
• You have expertise in monitoring and observability for ML systems, model versioning and experiment tracking, as well as experience with the requirements of edge deployments.
• You impress with strong system design, automation expertise, and operational leadership as well as the ability to drive cross-functional alignment.
• You are characterized by teamwork skills, communication skills, solution orientation, analytical thinking, willingness to learn, independence, and diligence.
• Very good German skills and very good English skills (written and spoken) round off your profile.

Contact and further information