Gia Le Viet is a Manager of Developer Relations at Google with 11 years of self-taught, cross-disciplinary engineering experience spanning machine learning (TensorFlow/TFLite), mobile (Android/iOS), web (Java/Node.js) and ERP systems. He combines hands-on work—contributing to high-profile TensorFlow projects like tflite-support and examples, where he implemented ImageClassifier and Android digit classification—with product and go-to-market skills as a PM for Google Cloud Imagen API. Based in California, he pairs public speaking and developer advocacy with practical engineering, bridging technical depth and storytelling to help teams adopt ML on edge devices. An unusual strength is his blend of low-level integration (adapting C++/Java bindings and audio buffer fixes) with developer-focused product narrative and launch strategy.
Contributions:2 releases, 96 reviews, 151 commits in 3 years 1 month
Contributions summary:Gia's contributions primarily involved adding missing files and implementing code for the digit classifier application. This included creating the `DigitClassifier.kt` class, modifying the `MainActivity.kt`, and integrating the MNIST TFLite model to build a handwritten digit classifier. The changes focused on enabling digit classification within an Android environment using TensorFlow Lite.
TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.
Role in this project:
ML Engineer
Contributions:308 reviews, 40 commits, 19 PRs in 1 year 11 months
Contributions summary:Gia contributed to the development and testing of the TFLite Support library, specifically focusing on the ImageClassifier and ObjectDetector tasks. Their work involved modifying existing test cases, adding new test scenarios and adapting the code to accommodate changes in the underlying C++ API. Furthermore, the user implemented the creation of the `ImageClassifier` from a file path and other related methods, suggesting an involvement in the integration of TFLite models. They also addressed issues in the Java side related to audio buffer processing.
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