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KEY EXPECTED ACHIEVEMENTS
Business understanding & Solution implementation
• The business need is understood and formalized in a descriptive datasheet or specifications
• The methods are identified through external researches and selected by their theoretical bases, advantages and drawbacks.
 

Roles & Responsibilities: 

-    Responsible for design and implementation of Application MLOPs frameworks.

- Responsible for Deploying the ML Model end to end

- Expert on Azure DevOps Pipelines
-    Responsible for Model and Data Drift frameworks.
-    Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects.
-    Experience in MLFlow.
-    Envision, implement and rollout best MLOPs/DevOps tools and automation.

- Nice to have LLMOPS knowledge