Hudson River Trading Algo Engineer, 2022
Facebook Software Engineer, 2019-2022
I spent my tenure at Facebook working on Monetization Integrity. In short, we decided whether an entity on IG/FB is monetizable or not using a mix of machine learning, heuristics, and human reviewers. My projects included:
- Staging a high-profile upgrade of our core monetization policies to align with industry standards.
- Pioneering machine learning models that forecast how risky a page is to violate our monetization policies
- Working closely with peer engineers, data scientists, product managers, and policy leads to understand and close gaps in our topline metrics
- Planning, collaborating, and executing on large infrastructure overhauls of our ML-based decision serving workflows.
Google Associate Product Manager Intern, Summer 2018
As an APM intern, I worked on the Assistant on automotive surfaces team. My project primarily focused on defining a new feature that will improve the daily experience of drivers. I explored use cases with other PMs, worked through design decisions with UX, and collaborated with engineering stakeholders.
Lyft Software Engineering Intern, Winter 2018
At Lyft I contributed to Express Drive and Fleet Management. On the express drive end, I improved product experience through tooling for vehicle geolocation, maintenance/collision servicing, and rental reposession. Within Fleet Management, I aided the deployment and querying of Elasticsearch indices on Lyft's autonomous and rental vehicles. Holistically, I matured my understanding of datastore management, frontend design patterns, API building, and architecting brand new microservices.
Amazon Software Engineering Intern, Summer 2017
Amazon Personalization houses an incredibly sophisticated product recommendation system, driven by years of A/B tests. One of the biggest challenges at Amazon scale is balancing recommendation quality with speed. I worked on incorporating more complex (and more relevant) recommendations in the parts of Amazon requiring low latency. My major deliverable was a NoSQL dataset of more than 100 million rows containing the preprocessed recommendation scores from a computationally expensive recommendation algorithm.
Google Software Engineering Intern, Winter 2017
As a member of cloud monitoring, I improved usability of the analytics pipelines through a new pipeline monitoring service. By storing pipeline statuses in a Spanner database, I made complex tasks such as diagnosing the root cause of a cascading pipeline automatic. My entrance into this program was quite unique, as I got my interview after completing the Google Foobar challenge. Check out my portfolio for what that is!
InternBlitz Technical Co-founder, Fall 2016-Fall 2017
InternBlitz is the common application for internships. I worked on the core functionality of the platform by architecting internship web scrapers, improving the application pipeline, launching a user dashboard, and maturing a messaging system prototype--all so that people could conduct an end-to-end internship search under one platform. InternBlitz was accepted into Georgia Tech's 2017 Startup Launch. I balanced my work with my internship at Amazon.
Vertafore Software Engineering Intern, Summer 2016
In the summer fo 2016, I worked with Vertafore on ImageRight, an insurance software that facilitates agent productivity. I helped integrate an array of cloud storage management solutions that are being implemented across all of the company's products. I also contributed to the initiative of providing high quality unit and end-to-end tests across the entire platform.