Worked on the ROCm/aiter repository to deliver RMSNorm exposure within the Aiter library, expanding its normalization capabilities for machine learning workflows. The work involved updating the Python package’s __init__.py to import rmsnorm operations and correcting the compile_ops mapping to reference rmsnorm_pybind.cu and rmsnorm_kernels.cu, ensuring proper CUDA binding integration. Using C++ and Python, the developer validated the integration path to enable seamless downstream usage of RMSNorm in training pipelines. This feature simplifies model integration and enhances training stability, reflecting a focused approach to library development and careful attention to build and runtime wiring within the ROCm/aiter ecosystem.