Worked on targeted memory management improvements in the TensorFlow Lite GPU path, focusing on enabling 16KB page size alignment for the shared library within the tensorflow/tensorflow repository. This feature was implemented through a single, production-ready C++ commit, designed to optimize memory usage and enhance performance on compatible hardware. The approach involved low-level GPU programming and careful integration with TensorFlow’s existing infrastructure, ensuring stable deployment and compatibility. Leveraging expertise in C++ development and GPU programming, the work addressed a specific hardware optimization need, laying the groundwork for broader performance gains in future TensorFlow Lite GPU deployments without introducing new bugs.