Maple Ong is a Staff Engineer based in New York with nine years of hands-on experience building and improving Ruby and Rails systems, currently leading backend work at Gusto. They have a strong open-source footprint across high-profile projects—contributing to Shopify tools like packwerk, tapioca, and ruby-lsp, as well as core Ruby and TruffleRuby—where they focused on refactors, language-server features, and VM/YJIT enhancements. Maple combines production engineering with deep language-level knowledge, having added methods to the Ruby core, improved compiler internals, and bolstered test suites for edge cases. Their background spans product companies and research-oriented roles, pairing pragmatic shipping at scale with careful attention to correctness and performance. Colleagues describe them as a thoughtful engineer who surfaces subtle edge cases (e.g., custom inflections and engine loading) and turns them into robust, maintainable code.
9 years of coding experience
7 years of employment as a software developer
Honours Bachelor of Science in Health Studies (B.Sc.) Co-op, Honours Bachelor of Science in Health Studies (B.Sc.) Co-op at University of Waterloo
Contributions:1 release, 49 reviews, 32 commits in 4 months
Contributions summary:Maple primarily focused on refactoring and improving the `packwerk` codebase. They made changes to the `Inflector` class, making it more testable and adding a new constructor. Additionally, the user updated the application validator and made necessary adjustments to the association inspector to incorporate the inflector changes. Several changes were related to custom inflections and how they're loaded and applied within the application, ensuring correct behavior for specific edge cases.
Contributions:1 release, 25 reviews, 99 commits in 5 months
Contributions summary:Maple primarily focused on enhancing the functionality and robustness of the Ruby LSP (Language Server Protocol) for Ruby. Their contributions include fixing breaking changes related to parser usage, refactoring code for better readability and maintainability, and adding comprehensive test cases to ensure code correctness. The user also implemented semantic highlighting features, a crucial aspect of LSP, and refined the tokenization process, demonstrating a deep understanding of language server architecture.
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