I will build mlops pipeline deploy ml model with docker azure ci cd and fastapi

Is your machine learning model stuck in a Jupyter notebook and not reaching production?

You are in the right place.

I build production ready MLOps pipelines that take your ML or AI model from notebook 

to a live deployed API that your team can actually use and monitor.

I am a Gold Medalist BS Data Science graduate and AI Developer with real production 

deployment experience. At Robx AI I deployed live LLM pipelines serving real users. At 

Systems Limited I worked with Azure DevOps CI CD pipelines and Docker in a production 

grade enterprise environment.

This is not theory. I build things that actually run in production.

What I will build for you:

Docker containerization of your ML model FastAPI REST endpoint for model serving

• CI CD pipeline with GitHub Actions or Azure DevOps
• Model deployment on Azure ML Hugging Face 
• Spaces or your preferred cloud
• MLflow experiment tracking and model registry
• Model monitoring and performance logging
• Automated retraining pipeline setup
• Clean documentation and handoff guide

Tech stack I work with:

• Docker and Docker Compose
• Azure ML and Azure DevOps
• GitHub Actions for CI CD
• MLflow for experiment tracking
• FastAPI for model serving
• Python Scikit-Learn