Description

You will design, build, and manage scalable machine learning pipelines and infrastructure on Azure.

This role is hybrid.

Responsibilities

• Design and implement ML pipelines using Azure ML, Databricks, and PySpark.
• Build automated CI/CD pipelines with GitHub Actions and enforce code quality via SonarQube.
• Containerize and deploy models using Azure Kubernetes Service (AKS) for high availability.
• Develop reusable templates for ML use cases and design robust APIs for model integration.
• Monitor data drift, optimize model performance, and manage costs for training and deployment.

Required Skills

• 5+ years of experience in MLOps or DevOps engineering.
• Hands-on expertise with Azure ML, Databricks, and PySpark.
• Proficiency in Azure Kubernetes Service (AKS) for container orchestration.
• Strong experience building CI/CD pipelines using GitHub and GitHub Actions.
• Ability to design and manage scalable APIs for ML model interaction.
• Understanding of ML architecture, data drift monitoring, and cost optimization strategies.

Key Skills

Education

Any Gradute