Implemented POC design for a resource manager, which assigns compute resources to distributed big data compute sessions within Meta AI/Spark infrastructure. Scale of 215M jobs and 15k users daily
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Optimized MySQL database, Thrift network, Java software performance to bring down e2e latency while supporting 10x vertical scale (100k to 1M+ concurrent sessions)
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Gathered metrics and bottleneck data to assess viability and strategic next steps for prototype
Worked with React, Typescript, and Tailwind to collaboratively implement various public-facing static sites. Implemented animations manually and with various animation libraries.
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Built interactive, animated hacker applications tool used to submit 8000+ applications
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Built RSVP tool and integrated with our backend to support 1000+ hackers in real time
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Participated in design reviews and discussions, as well as process and project retrospectives
Designed software and process to support product boosting, which complements ML-based product ordering along Uber's core ride request flow. Impacts ~525 million ride requests per month worldwide
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Restructured boosting configuration to allow for better governance, monitoring, and data aggregation. Oversaw migration of ~100 currently boosted products between configurations.
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Iteratively designed and implemented UI/UX flow to reshape internal processes for requesting product boosts
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Consulted with operations, product, backend engineers and ML engineers to scope, design, and deliver tooling over the course of the internship
Education
2019 — 2024
University of Waterloo
Bachelor of Engineering - BE
2019 — 2024
2022 — 2023
The Hong Kong University of Science and Technology
