AI/ML Ops Engineer (w/m/d)

Job summary

The AI/ML Ops Engineer ensures stable, scalable operation of machine-learning and generative AI systems, building delivery workflows from development through production. Responsibilities include CI/CD/CT pipelines, model registries and deployment processes, running AI services with Docker and Kubernetes, and monitoring model drift, latency, cost, and availability. The role also supports repeatable ML workflows, audit-ready documentation, and collaboration with data science, engineering, and platform teams.

Benefits

Qualifications

• Several years of experience in DevOps or MLOps
• Strong knowledge of Docker and Kubernetes
• Experience with CI/CD systems and automated deployments
• Practical experience with monitoring, logging, and tracking tools
• Good Python skills for process automation
• Experience operating LLMOps or generative AI applications
• Knowledge of relevant standards such as ISO/IEC 42001
• Experience with hybrid cloud and on-premise environments

Responsibilities

• Build and operate CI/CD/CT pipelines for machine-learning models and generative AI applications, including prompt workflows
• Implement and manage model registries, versioning, and deployment processes
• Deploy AI services to production using Docker and Kubernetes
• Monitor and optimize model drift, latency, cost, and availability
• Ensure ML workflows are scalable, stable, and repeatable
• Create audit-ready model cards, logs, and documentation
• Collaborate with data scientists, AI/ML engineers, and platform teams
• Develop best practices for MLOps and AI operations

Skills

Degrees

Work schedule

Industry

Relocation