Azure DevOps & MLOps Engineer

Roles and Responsibilities: Design, implement, and maintain CI/CD pipelines using Azure DevOps. Deploy, manage, and optimize containerized applications and workloads using Azure Kubernetes Service (AKS). Build and support machine learning deployment workflows using Azure Machine Learning. Implement Infrastructure as Code (IaC) to automate cloud infrastructure provisioning and configuration. Develop and maintain automated build, testing, deployment, and release processes. Support MLOps practices, including model deployment, versioning, monitoring, and lifecycle management. Apply cloud security best practices and support compliance requirements across Azure environments. Collaborate with development, data science, and infrastructure teams to streamline application and ML model deployments. Integrate cloud-native solutions with existing enterprise IT infrastructure.

Required Qualifications: Strong hands-on experience with Microsoft Azure DevOps. Practical experience deploying and managing Azure Kubernetes Service (AKS). Experience with Azure Machine Learning and AI/ML deployment workflows. Proficiency in CI/CD pipeline development and automation. Strong knowledge of Infrastructure as Code (IaC) and cloud infrastructure automation. Experience with Docker, Kubernetes, and container orchestration. Understanding of Azure cloud security best practices and compliance frameworks. Knowledge of traditional IT infrastructure and enterprise application environments.