Jodi Jang is a Software Engineer II based in New York with three years of professional experience building full-stack, production-grade systems. She drove a major improvement at Sentry by leading cross-team work to integrate ML similarity embeddings, reducing duplicate error noise by 96% and collaborating with data science to surface high-confidence archived issues. Her contributions span front-end React/TypeScript work and backend data-model changes in a well-known open-source project (getsentry/sentry), evidencing comfort across the stack. Prior internships at Ford, Sunnybrook, and Thales show a pattern of shipping UI and data automation solutions using C++, QML, Python, R and analytics tooling. Now at Meta, she brings practical ML+engineering experience and a track record of turning complex telemetry and sensor problems into reliable, user-focused features.
3 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of Toronto Scarborough
Developer-first error tracking and performance monitoring
Role in this project:
Full-stack Developer
Contributions:629 reviews, 64 commits, 536 PRs in 2 months
Contributions summary:Jodi contributed to the Sentry codebase by implementing and modifying both front-end and back-end components. Their work involved changes to issue details, alert rule UIs, and code owner settings, which suggests involvement across multiple parts of the application. Their commits indicate a focus on JavaScript/React front-end work with modifications to Typescript. Additionally, their modifications touch on the backend by altering data models related to the system.
Contributions:1 PR, 36 pushes, 8 branches in 10 months
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