Muhammed Nuzumlalı is a Machine Learning Engineer at Apple with 11 years of software engineering experience blending mobile engineering, ML research, and open-source contributions. He has led iOS teams and modernization efforts—introducing testing, CI, code review practices, a shared internal iOS framework, and company-wide migration from CVS/SVN to Git—while building large consumer apps for major Turkish brands. His work spans production ML systems for user engagement (lead at Netmera) and pragmatic SDK and tooling improvements, including meaningful backend and packaging contributions to widely used CocoaPods projects. Comfortable bridging research and product, he pursued advanced CS studies at Yale and Boğaziçi and has experience in ML/NLP research paths. Known for improving developer experience and reliability, he pairs deep platform-level insight with a knack for shipping robust, developer-friendly libraries.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Dropped, Doctor of Philosophy - PhD, Computer Science, Dropped at Yale University
Bachelor’s Degree, Computer Engineering, 3.42/4.00, Bachelor’s Degree, Computer Engineering, 3.42/4.00 at Boğaziçi University
CocoaPods plugin which allows you to generate a static library from a podspec.
Role in this project:
Full-stack Developer
Contributions:37 commits, 6 PRs, 30 pushes in 2 years 6 months
Contributions summary:Muhammed primarily focused on enhancing the `cocoapods-packager` plugin, a tool for generating static libraries from podspecs. Their contributions involved modifying the `SpecBuilder` class to support new attributes like `weak_frameworks` and multiline string attributes. Additionally, the user added support for including vendored libraries and frameworks, improved testing, and updated the packaging command for local pods. These changes improve the plugin's functionality and flexibility.
Contributions:80 commits, 31 PRs, 59 pushes in 6 years 2 months
Contributions summary:Muhammed primarily focused on improving the CocoaPods dependency manager's internal logic and error handling. Their contributions included adding informative error messages for dependency conflicts, enhancing the search index format for faster searches, and refactoring update logic within the codebase. Furthermore, the user added a minimum deployment target option and improved the copy resources script. This work demonstrates a strong understanding of the project's core functionality and a commitment to improving user experience through better error messaging and performance enhancements.
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Muhammed Nuzumlalı - Machine Learning Engineer at Apple