MLOps Engineer

Responsibilities

• Implement CI/CD pipelines for continuous code integration (DevOps) and model delivery (ModelOps)
• Automate the creation of resources and deployment pipelines using SDKs and Azure DevOps
• Configure project archetypes in code to integrate with Azure Machine Learning services
• Enable local or remote development against Databricks clusters or Azure Machine Learning compute
• Automate all project configurations and deployments

Requirements

• 2-3 years of experience as a DevOps specialist leading CI/CD pipelines with Azure DevOps
• Experience with Infrastructure as Code (IaC) for environment automation
• 3-5 years of experience as a Software or Systems Engineer developing applications or environment configuration scripts
• Proficiency with Azure DevOps (Boards, Pipelines, Repos, Test Plans, Artifacts)
• Experience with Azure services (Key Vault, Managed Identities, Application Insights, Azure Monitor, App Service, Storage)
• Experience with Azure Machine Learning (Experiment Tracking, Model Registry, AML SDK v2, MLflow)
• Experience with IaC tools (Terraform, Bicep, Docker, Powershell, Scripting)
• Experience with QA & Testing tools (Kiuwan, JMeter, PyTest)
• Proficiency with Visual Studio Code, Git, and GitFlow

Preferred Qualifications

• Previous experience in Data & AI environment industrialization
• Experience with Bicep, Terraform, or Databricks API
• Knowledge of Azure Data Factory, Cosmos DB, or SQL Databases
• Experience with Databricks (Delta Tables, Unity Catalog, Databricks Connect)
• Python development skills (Click, Poetry, Pipx, Opencensus, Black, Pdb+, FastAPI)

About the Company

En WayOps is looking for an MLOps Engineer to join a top-tier Data & AI team working on cloud projects with the latest technologies.