Worked on the pytorch/pytorch repository to enable foundational interoperability between C++ and Python layouts, specifically targeting Torch-spyre integration. Developed a typecaster bridging c10::layout in C++ with torch.layout in Python, using Pybind11 to facilitate seamless data exchange. This addition established the basis for layout-aware tooling, profiling, and debugging within the PyTorch core, reducing integration friction for downstream projects. The work involved close cross-team collaboration and compliance with contribution requirements, as reflected in the CLA-compliant pull request. Demonstrated proficiency in C++ development, Pybind11, and Torch library internals, setting the stage for future enhancements in layout-based performance analysis.