Experience
2024 — Now
2024 — Now
San Francisco, California, United States
✍🏽 doing taxes
2022 — 2024
2022 — 2024
San Francisco, California, United States
Application Architecture & Performance - making Rippling ⚡ fast and highly scalable
2020 — 2022
2020 — 2022
San Francisco, California, United States
Enterprise Scaling Team in Core Infrastructure Area
I lead a large effort to expand Asana's data center offering and infrastructure to APAC for Enterprise data residency requirements. I worked with almost all of our infrastructure teams to ensure that this process would be easy, toil-free, and repeatable for future infrastructure expansion efforts. Our team is now able to quickly launch new data centers without compromising stability or engineering velocity.
I lead multiple projects and worked with our largest Enterprise customers as part of a cross-functional effort to build Asana Enterprise Key Management. I helped design and ship Comprehensive Key Verification, Encrypted Attachments, and systems to automatically handle revoked keys.
I worked briefly on the Asana Microservices Framework, Service mesh and Envoy proxy. As Microservices Oncall lead I helped revamp our service metrics, dashboards, and define our uptime SLOs.
Outside of Program Work
* I built the Sorting Hat - our early career team matching tool
* I proposed an Engineering Rotation program for cross-pollination and IC growth that I helped implement as an Engineering Org Initiative
* I helped champion Terraform at Asana, identified and roadmapped key Infrastructure-as-Code initiatives.
2019 — 2019
2019 — 2019
Seattle, Washington
Facebook Search Team
I worked on improving spelling correction using phonetics and unsupervised ML methods for search.
2018 — 2019
La Jolla, CA
I was an undergraduate research assistant at the Statistical and Visual Computing Lab at UCSD. I joined the Plankton Imaging project advised by Dr. Nuno Vasconcelos.
The goal of the project was to be able to determine the family of a given several hundreds of images of a plankton specimen. The caveat is that in such biological problems, there is not a diverse wealth of specimen for each taxonomic family of plankton. We are comparing the performance of various state of the art 3D object recognition models as applied to this 'low-shot learning' biological problem.
http://www.svcl.ucsd.edu
Education
UC San Diego