Azure DevOps & MLOps Engineer

Veriipro; Woburn (MA); On-site; USD 130,000 - 190,000; Full time

Job summary

Veriipro in Massachusetts is seeking an experienced Azure DevOps & MLOps Engineer to design, implement, and maintain cloud-based DevOps and ML infrastructure in the Azure ecosystem.

The role emphasizes building automated CI/CD pipelines, deploying AKS workloads, and advancing IaC, security, and MLOps across enterprise environments.

Qualifications

• Strong hands-on experience with Microsoft Azure DevOps.
• Experience deploying and managing AKS.
• Experience with Azure Machine Learning and AI/ML deployment workflows.
• Proficiency in CI/CD pipeline development and automation.
• Strong knowledge of IaC and cloud infrastructure automation.
• Experience with Docker, Kubernetes, and container orchestration.
• Understanding of Azure cloud security best practices and compliance frameworks.

Responsibilities

• Design, implement, and maintain CI/CD pipelines using Azure DevOps.
• Deploy, manage, and optimize containerized applications and workloads using 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.

Skills

Azure DevOps

AKS

Azure Machine Learning

CI/CD automation

Infrastructure as Code

Cloud security

Container orchestration

MLOps

Tools

Docker

Kubernetes

Job description

Position Overview

We are seeking an experienced Azure DevOps & MLOps Engineer to design, implement, and maintain cloud-based DevOps and machine learning infrastructure within the Microsoft Azure ecosystem.

The ideal candidate will have strong hands-on experience with Azure DevOps, Azure Kubernetes Service (AKS), and Azure Machine Learning, along with expertise in CI/CD automation, Infrastructure as Code (IaC), container orchestration, and cloud security.

This role will focus on building and optimizing automated deployment pipelines, supporting scalable AI/ML workloads, and integrating modern cloud engineering practices with traditional IT infrastructure.

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.