• Currently working on Video and Audio Similarity Understanding for Copyright protection and Recommendation quality for FB, IG and Messenger.

• In 2023 and mid 2024, I was in the Research Platform team at Meta, where we were building a crowdsourcing data collection and research platform. As the payments pillar TL, I led a successful migration to a more reliable payments provider, enhancing the payment experience for over 60% of our users, in close collaboration with legal, privacy, UX, and PM partners along with external payment vendors.

• In 2021 and 2022, was in the Metrics Governance team and led the design and development of the Governance Plane, a new automated system that assesses metric risks for standard infrastructure components utilized at Meta and Instagram.

• Designed and implemented key initiatives for VMware’s Network Virtualization product (NSX) including time-based firewall and URL filtering based on reputation and category.

• Built a monitoring framework which collected stats like session count, reputation and category of outgoing URL traffic from an NSX datacenter.

• Designed and implemented the framework to migrate customers from NSX V (older ESX only platform) to NSX T (new multi-hypervisor supported platform)

Technology used: Java, Python, Spring, ElasticSearch, AWS Lambda

As part of the Consumer Onboarding team, I developed a dashboard which provides location based analytics of the whole process of onboarding a customer onto PayPal.com. It has two components

• Analytics Portal : It is a map based dashboard that aggregates events while onboarding a user to paypal.com. It collects the events from the past one hour and then visually represent them by geo location.

• Real time feed: This application shows all consumer onboarding events happening in real time across the globe as pin points at the actual location.

Worked on the backend systems for Appointment bookings and searching doctors at Practo.

• Worked on PayPal’s Behavioral Activity tracking platform which was designed to process events generated from user activity. It leveraged the lambda architecture using Hadoop MapReduce for batch processing and Apache Storm for realtime processing.

• Built an email alerting system in Python for monitoring the status of various components of the analytics platform. This helped in identifying issues with any components before it spiraled into major problems.

• Developed an end-to-end data integrity application for the analytics platform. It queried metrics from PayPal’s central logger and executed a Map Reduce job for calculating the metrics count from HDFS cluster. This helped in monitoring the overall health of the platform.

• Established a CI pipeline for our code repositories with pre-commit hooks, automated testing and continuous deployment using Jenkins. Used Cobertura, Jacoco, FindBugs plugins to improve coverage and code quality. This helped minimize the build/deploy time and thus ship code faster.

Technology used: Java, Python, Hadoop Map Reduce, HDFS, Storm, Zookeeper, Maven, Jenkins