Over the course of the year, I implemented and maintained features of an ML training platform that is used by 5000+ employees at Meta. Fluent2 is a declarative API for creating and testing ML models on Meta’s workflow engine. It also offers hyperparameter sweeps and metrics. Looper is a pipeline service that allows you to create, model, train, deploy, and monitor an ML solution on Meta prods.

I owned and designed a generic shadow migration service to facilitate transformer migration work in Fluent2 and Looper. In addition to this, I implemented and designed a microservice to collect resource information for feature collection and extraction.

I have done several shifts to provide 24h on-call support to the Meta community regarding Fluent2/Looper inquiries and maintained healthy daily releases.

Over the course of a year, I worked on a small team of 3 engineers to implement and maintain features for the back-end and front-end of a load testing and a preview deployments platform used by 1000s of users within Spotify. Additionally, I wrote up and presented RFCs and ADRs to provide guidance regarding system design decisions. Within a 3 person rotation, I provided on-call support to the global Spotify engineering community for a set of tools within the web testing space. As a team, we supported to roll-out high-profile products used by 500+ million users. Individually, I owned the design and implementation of a web E2E testing microservices.

Over the course of about a year, I worked on a team developing the back-end (Python) and front-end (Vue) of an NLP, web application used to summarize multiple MRI reports from a single patient. In addition, I optimized the original architecture of the application to account for future race conditions. This application reduced the time required for doctors to generate these MRI summaries from the technical MRI reports by 70% through the use of this application.

Over the course of my time at the Global Business Service branch of IBM, I have worked on various projects for companies involved in telecommunications, oil, government, and the automotive industry. Within these projects I have worked primarily as a back-end developer (Java (specialty), Node.js, Python), front-end developer (React) and data scientist (Python).