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Azure AI DevOps Engineer

  • Source: Naukri
  • Tata Consultancy Services
  • On-site
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Role- Azure AI DevOps / MLOps Engineer

Experience: 8-10 Years

Location- Pan India

Job Description-

We are looking for an experienced Azure AI DevOps / MLOps Engineer to design, implement, and maintain CI/CD and MLOps pipelines for cloud, AI, and Machine Learning workloads. The candidate should have strong Azure DevOps experience along with hands-on knowledge of Azure Machine Learning and production AI/ML deployments.

Roles & Responsibilities

  • Design and manage CI/CD pipelines using Azure DevOps.
  • Build automated MLOps pipelines with Azure Machine Learning for model training and deployment. [learn.microsoft.com], [learn.microsoft.com]
  • Automate provisioning of Azure infrastructure using Terraform / Infrastructure as Code.
  • Manage model deployment, versioning and production monitoring.
  • Implement source control and branching strategies using Git.
  • Containerize AI/ML applications using Docker and support Kubernetes-based deployments where required.
  • Manage Azure security, authentication, RBAC and service connections.
  • Implement monitoring, logging and troubleshooting for production workloads.
  • Collaborate with Data Scientists, AI Engineers, Cloud Architects and DevOps teams.
  • Support deployment automation across development, testing and production environments.

Mandatory Skills

  1. Azure DevOps
  2. CI/CD Pipelines
  3. Microsoft Azure
  4. Azure Machine Learning
  5. MLOps
  6. Terraform / IaC
  7. Docker
  8. Kubernetes / AKS
  9. Git
  10. Python / scripting

Good to Have

  • Azure AI services
  • MLflow
  • Azure Container Registry
  • Azure Monitor
  • Key Vault
  • Azure CLI
  • GitHub Actions
  • GenAI / LLM deployment exposure

Skills

  • microsoft-azure
  • azure-devops
  • azure-machine-learning
  • Terraform
  • Docker
  • Kubernetes
  • azure-rbac
  • Python
  • ml-flow
  • mlflow
  • microsoft-azure-container-registry
  • azure-monitor
  • vault
  • Github
  • github-actions

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