MLOps Engineer - MLFlow / Azure Databricks

Your Responsibilities:

• Set up and configure MLFlow tracking, model registry, and artifact storage for both on-prem and Azure environments
• Integrate MLFlow with Databricks and/or on-premise infrastructure
• Ensure secure access, data protection, and compliance with internal policies and governance standards
• Enable MLOps automation by supporting CI/CD pipelines for ML models using tools such as Azure DevOps or GitHub Actions
• Define and implement workflows for model training, validation, deployment, and monitoring
• Collaborate closely with data scientists and platform engineers to operationalize machine learning models effectively
• Produce detailed documentation of setup processes, workflows, and best practices
• Contribute to the design of the target MLOps architecture and assist with migration planning to Azure Databricks

Your Profile:

• Proven hands-on experience with MLFlow, both on-premise and in cloud environments
• Good understanding of Azure Databricks and its MLFlow integration
• Strong background in MLOps tooling, including CI/CD, model lifecycle management, and monitoring
• Familiarity with security, governance, and compliance within ML workflows
• Excellent communication and technical documentation skills
• Fluent in English (written and spoken)