Backend developer, primarily working on the Order Management System (OMS) for placing trades and on stock pledging services.

Team: Revenue and GrowthWorked in the Offers Team which creates all the discount run on Swiggy across business-lines.My Task was to optimize the storage and searching of offers stored in Elasticsearch. The legacy feature stored Terabytes of offers data only in few elasticsearch indices. A simple search operation for gathering/deleting an offer required browsing through Terabytes of offers data.The following features were added to improve the search process: 1. Changes were made to Elasticsearch data ingestion pipeline for automatically creating time-based (quarterly) indices.2. Added Code for Searching offers in a given timestamp range.3. Added the Functionally for deleting offers in old ES Indices through the ILM policy defined in ES Index Templates.Apart for Adding these features I learnt a lot about How to do unit and functional testing, process of deployment and testing of code on Prod. and Non-Prod. Environments And In general the best practices of development from some of the smartest people at Swiggy.

Team: System Intelligence/Knox AI, On-Device AIThe Team worked towards developing a Reinforcement Learning based solution for solving the problem of power drain while playing YouTube Videos on Samsung Galaxy Devices.

Have been Teaching Assistant (TA) for the course : BITS F312-Neural Networks and Fuzzy LogicConducted workshops, helped in creating meaningful assignments and stimulating quizzes for 100+ students enrolled in the course.Guided students on implementation of leading research papers in machine learning as a part of their term project.