Sep 2021 – Jul 2024 · 2 yrs 10 mos · Bengaluru, Karnataka, India · Remote

• Led the implementation of end-to-end MLOps practices, including data drift analysis, experiment management with MLflow, and model registry establishment, ensuring model accuracy and reliability in production environments.
• Streamlined development processes by enhancing CI/CD pipelines with automated code quality tests and Databricks workflow deployment, optimizing efficiency and reliability throughout the machine learning lifecycle.
• Implemented comprehensive monitoring and alerting systems, including prediction drift monitoring and SMTP email notifications, to ensure timely response to critical events and maintain model performance over time.
• Established versatile MLOps governance framework,utilizing Databricks, MLFlow, GitHub, and
• GitHubActions for end-to-end automation.
• Devised robust CI/CD strategy, rigorously validating code and enabling seamless deployment to Databricks across environments.
• Spearheaded MLOps, automating project lifecycle with MLFlow, Azure DevOps, PyCharm, Databricks, and Azure Data Factory (ADF).
• Created extensive unit tests using unittest, ensuring code integrity and adherence to best practices.
• Engineered PySpark data processing framework on AI driven platform, orchestrating data flow using Airflow, Databricks, GCP, SSMS, and Docker.
• Led enhancements of Azure-hosted Python Dash web app, fixing bugs and adding client-focused features, enhancing UX.
• Optimised SQL DB efficiency via aggregated views, reducing load times and boosting performance.

Jul 2018 – Aug 2019 · 1 yr 1 mo · Vellore, Tamil Nadu, India