About the Role
For an Enterprise AI project, an experienced MLOps Engineer is sought. The goal is to build and operate compliant, scalable end-to-end Machine Learning workflows from development to productive use.
Conditions:
- Start: ASAP
- Duration: End of 2026, extension possible
- Workload: 100%
- Work Model: Remote preferred, occasional on-site appointments by arrangement
Responsibilities
- Building and operating end-to-end Data Science and ML workflows
- Implementing ML orchestration solutions (e.g., Kubeflow Pipelines)
- Integrating ML tracking and experiment tools (MLflow, TensorBoard, or similar)
- Automating training, deployment, and monitoring processes
- Developing and maintaining Python-based ML applications
- Implementing CI/CD and GitOps principles for ML pipelines
- Ensuring Security & Vulnerability Management for code, containers, and models
- Operating and further developing productive AI applications
- Integrating regulatory frameworks (e.g., AI Act, internal policies, customer requirements)
- Coordinating with platform, business, and project teams, including expectation management
Requirements
- Several years of experience as an MLOps Engineer, ML Engineer, or Data Engineer
- Very good knowledge of Kubernetes-/OpenShift-based environments
- Experience with ML orchestration, ML tracking, and monitoring
- Very good Python skills
- Very good German and English language skills