I am a software engineer on the anti-scraping team at Meta. My team owns the rate limiting infrastructure for Facebook, Instagram, and Oculus. I also own the request logging platform that helps determine rate limiting thresholds and develop machine learning models to identify bots.

I’ve previously also worked on the Facebook Attribution product that helped advertisers measure the effectiveness of their ads.

Graduate Teaching Assistant for CS3214 - Computer Systems, a course that introduces design approaches in operating systems, inter-process communication, multithreading, and network protocols as relevant to modern web applications. My responsibilities include:

• Hold office hours where students can get their questions clarified

• Conduct tutorials to introduce assignments and projects

• Grading assignments, projects, and exams

• Setup auto-grading infrastructure for projects and assignments

Worked on NLP and Dialog Systems for Facebook Messenger

• Developed a neural coreference resolution system for Facebook Messenger's "M" chatbot

• Created a data annotation tool for identifying named entities and linking them as co-referent

• Integrated the neural coreference resolution system into a hierarchical sieve-based classifier that allowed for the addition of rules to handle edge cases

• Pushed the neural network model to production

I worked with the Cloud Engineering and PaaS team which spearheaded the hybrid cloud journey at PayPal. I worked on PaaS Infrastructure Manager (PiMan), an application to create Mesos-based clusters in a cloud agnostic fashion. PiMan automates provisioning, service discovery, scaling, upgrade, monitoring, alerting and remediation for these clusters in an immutable fashion. PiMan was built on Java and MongoDB, relying on Terraform, Packer and Consul for provisioning, packing images and service discovery respectively. Some of the highlights from my work here are:

• Designed and developed a Chaos Monkey framework to inject failures into and test resiliency of PiMan provisioned infrastructure. The different kinds of failures included shutdown, destroy and process termination. The termination schedule could be randomized to mimic real world scenarios.

• Implemented MDC logging for PiMan for distinguishing interleaved log outputs from parallel threads.

• Setup ELK stack for real time information mining and log visualization

I also developed proxC, an application to manage project lifecycle in Google Cloud Platform. The application was self-service where users could perform CRUD operations on GCP projects. I built the application ground-up with SSO integration and well defined authorisation roles. proxC adopted a 3-tier architecture where the API layer was written using the Dropwizard framework (Java 8), the UI layer using Angular 4 and the database as MongoDB.

I interned with the Platform-as-a-Service (PaaS) team at PayPal where I worked on containerization of PayPal applications using Docker. The highlights of my work here include:

• Automated the deployment of applications of different stacks (Node.JS and Java) on the developer's computers or virtual machines

• Demonstrated a proof-of-concept where multiple applications of different stacks can be run on the same machine, improving resource efficiency

• Enhanced the functionality of a ReST service to promote PayPal microservices from QA to Production by including support for Docker-based applications