Claire Wang
L4 Software Engineer at Netflix
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolClaire Wang is an L4 software engineer based in San Francisco with 11 years of experience building reliable backend and infrastructure systems. Currently at Netflix, she has progressed through media workflow infrastructure to broader platform responsibilities, demonstrating steady impact in production environments. An active open-source contributor, Claire has made substantive backend improvements to Tailscale’s WireGuard-based VPN stack—refactoring netstack APIs to eliminate classes of bugs and adding time-tracking primitives integrated across the codebase. Her earlier work includes test automation and maintenance for MALLET’s statistical NLP codebase, showing attention to quality and robust engineering practices. A UPenn computer and information science graduate, she combines systems-level networking expertise with a disciplined approach to testing and long-lived service reliability.
11 years of coding experience
B.S.E, Computer and Information Science, B.S.E, Computer and Information Science at University of Pennsylvania
Chinese, English
Github Skills (21)
unit-testing10
vpn10
back-end-development10
testing10
networking10
java10
wireguard10
javas10
junit10
go10
backend10
test-automation10
tailscale9
concurrency9
auth8
Programming languages (10)
Github contributions (5)
tailscale/tailscale
Nov 2022 - Dec 2022
The easiest, most secure way to use WireGuard and 2FA.
Role in this project:
Backend Developer
Backend DeveloperContributions:48 reviews, 2 commits, 83 PRs in 23 days
Contributions summary:Claire's commits primarily focus on modifying the `wgengine/netstack` and related files to improve the Tailscale's VPN functionality. They refactored the netstack API to require a `LocalBackend`, eliminating a class of bugs. The user also added a `Since` method to the `tstime` package and integrated it into several other modules like `logtail`, `ipn`, `derp`, and `control`, and the codebase to update usage of time-related methods. These changes suggest a focus on core backend logic and the network infrastructure.
secureprivacysecurityvpnwireguard
mimno/Mallet
Oct 2017 - Dec 2017
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 6 PRs, 7 comments in 2 months
Contributions summary:Claire's commits primarily focus on refactoring and updating test cases within the `mallet` repository. They modified existing tests for various data structures and components, including `Alphabet`, `PagedInstanceList`, `LabelVector`, and others. The changes primarily involve removing unnecessary elements and adjusting imports, indicating a focus on maintaining and improving the test suite.
extractionmalletlanguage-processingdata-miningsemantics
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