Song Song is a Senior Software Engineer based in the San Francisco Bay Area with 11 years of professional experience and an M.S. in Computer Science from The George Washington University. Currently at LinkedIn after roles at Amazon (AWS RDS) and other firms, he blends back-end systems work with front-end UI craftsmanship. He contributes to notable open-source projects like Jellyfin, implementing lyrics APIs and Roku client UI features, demonstrating comfort across BrightScript, C#, and React. Song’s background shows a pattern of shipping production services and media-focused integrations, and he often bridges server-side API design with polished client experiences. A practical problem-solver, he pairs academic rigor with hands-on contributions to community-driven software.
11 years of coding experience
4 years of employment as a software developer
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at The George Washington University
Contributions:4 releases, 499 reviews, 261 commits in 8 months
Contributions summary:Song primarily contributed to the development of the Roku client's user interface. Their commits focused on implementing and modifying UI components, including the creation of a music artist view, album details, and supporting elements like a progress bar. The changes involved modifying and adding BrightScript code within various component files to build out the music library UI and playback controls.
The Free Software Media System - Server Backend & API
Role in this project:
Back-end Developer
Contributions:33 reviews, 53 commits, 2 PRs in 17 days
Contributions summary:Song focused on implementing and enhancing the lyrics functionality within the Jellyfin media server. They added a lyrics API endpoint, created data models for lyrics, and implemented methods to retrieve lyrics from both .lrc and .txt files. Further contributions include modifications to existing controllers to integrate the new lyrics API and refactoring code for improved efficiency. They also updated project dependencies, specifically including a LrcParser library.
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