Azure Devops & Mlops Engineer

Connvertex Technologies • Woburn, MA

4d

About The Position

We are seeking an experienced Azure DevOps & MLOps Engineer to join our team. This role is crucial for designing, implementing, and managing our Azure DevOps pipelines and cloud infrastructure, with a specific focus on AI/ML model deployment and management. You will collaborate closely with data science and IT teams to ensure the rapid, secure, and scalable deployment of machine learning models and enterprise systems. Your responsibilities will include automating build, test, and release processes, managing Azure environments including AKS and GPU-enabled pools, enforcing security and compliance, and supporting the overall reliability and scalability of our platforms.

Requirements

• 5+ years in DevOps/SRE, with 3+ years on Azure.
• Hands on with Azure DevOps (Repos, Pipelines, Artifacts), GitHub Actions, and YAML based CI/CD.
• Strong IaC skills (Terraform or Bicep/ARM); experience managing AKS and container registries (ACR).
• Proficiency with PowerShell and/or Python for automation; familiarity with Docker and Helm.
• Experience operating Azure Machine Learning (workspaces, endpoints, registries) and integrating ML workflows in CI/CD.
• Solid understanding of cloud security (RBAC, Key Vault, Managed Identity, policies), networking (VNet, subnets, Private Link), and cost management.

Nice To Haves

• Experience with GPU workloads on AKS or AML; model serving (Azure ML Managed Online Endpoints, Kubernetes Inference).
• Familiarity with Databricks, Fabric, or other data platforms that feed AI services.
• Certifications: Azure DevOps Engineer Expert, Azure Solutions Architect, or equivalent.

Responsibilities

• Design and maintain Azure DevOps pipelines (YAML) for build, test, security scanning and release of AI/ML models.
• Implement Infrastructure as Code (IaC) using ARM templates, Terraform, or Bicep.
• Manage artifact repositories and container image signing for compliance.
• Administer Azure environments, including AKS clusters for containerized workloads and GPU-enabled pools for ML training.
• Standardize environments for business applications and Azure Machine Learning workspaces.
• Enforce governance guardrails for both IT and AI workloads.
• Ensure adherence to regulatory and internal security standards.
• Partner with data science teams to enable rapid deployment of ML models.
• Work with IT stakeholders to maintain reliability and scalability of enterprise systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed