As a Machine Learning Engineer, I am responsible for leading the ML Templates team that builds out ready-to-deploy ML templates that are easily integrable within the end-to-end strategic ML platform within the Bank.In addition to this, I also take great interest in leading various cross-team collaborative Experimental Gigs and contribute to the Open Source Programme Office (OSPO) within the Bank to foster a culture of promoting InnerSourcing and OpenSourcing of code.

As a PhD Scholar at DaSHLab, BITS Pilani Goa Campus, I work on exploring real-world applications of Federated Learning while integrating an MLOps perspective. My research focuses on optimizing the deployment and management of decentralized machine learning models across diverse, privacy-sensitive datasets. This involves developing scalable, secure frameworks that enable collaboration without compromising data security or model performance. My role as a researcher requires me to bridge the gap between cutting-edge theory and practical implementation, ensuring that Federated Learning systems can be seamlessly integrated into industry workflows. Additionally, I collaborate with academic and industry experts to push the boundaries of what is possible with decentralized AI technologies.

Architected an AWS workflow using Bedrock and serverless apps for GenAI capabilities to generate global claim set documents in multiple languages from core message elements in medical Research & Development papersDevelopment of an MLOps platform using AWS for Intelligent Clinical Trials at PwC Innovation Hub, primarily using serverless application templates

Data and Analytics Business Unit:Development of Data Science Labs on AWS Cloud for ML model training using SageMaker Notebooks, Training Jobs, Elastic Compute Cloud (EC2) and Elastic Map Reduce (EMR) clustersCarried out Data Engineering tasks like data summarisation, query and analysis of data from AWS S3 Data Lake using HiveQL to be further used by AWS EMR clusters to run Spark jobs on a regular basisDevelopment of Python and PySpark scripts to carry out end-to-end pipeline validations, and working with AWS Glue Crawlers for ETL tasksDevelopment and delivery of an efficient workflow for MLOps on AWS Cloud for deployment of trained ML models in production scale using SageMaker Batch Inferencing, Lambda Functions, Step Function, Code Build, Code Pipeline and Elastic Container Registry for Docker ImagesEnterprise Solutions Business Unit:Murex developer in Treasury Management System project to provide technology solutions in trading, treasury, risk operations for financial markets

Worked and trained on Digital Design using XILINX FPGA Technology

Worked and extensively trained on the applications of AngularJS