Freelance MLOps Engineer

• Build and operate end-to-end data science and machine learning workflows
• Implement ML orchestration solutions such as Kubeflow Pipelines
• Integrate ML experiment tracking and monitoring tools (MLflow, TensorBoard, or similar)
• Automate ML training, deployment, and monitoring processes
• Develop and maintain Python-based machine learning applications
• Implement CI/CD and GitOps practices for ML pipelines
• Ensure security and vulnerability management for code, containers, and ML models
• Operate and continuously improve production AI systems
• Ensure compliance with regulatory requirements (e.g. EU AI Act, internal policies, customer requirements)
• Coordinate with platform, engineering, and project teams, including stakeholder and expectation management

• Several years of experience as an MLOps Engineer, ML Engineer, or Data Engineer
• Strong hands-on experience with Kubernetes and/or OpenShift
• Proven experience with ML orchestration, experiment tracking, and monitoring tools
• Very strong Python development skills
• Experience working in enterprise or regulated environments is highly desirable
• Fluent German and English (spoken and written)

Experience working in enterprise or regulated environments is highly desirable

• Long-term, stable contract until 2026
• Remote-first working model
• Competitive daily rate
• Opportunity to work on a high-impact enterprise AI programme
• Modern MLOps stack and production-grade ML systems