Worked on the NVIDIA/cuda-quantum repository to enhance quantum kernel management by implementing deferred loading of registered C++ kernels in Python, introducing a LinkedKernels class, and updating decorators for improved efficiency. Addressed stability by strengthening SROA optimization with additional safety checks and developing new regression tests to prevent memory corruption during quantum operations. Improved module resolution accuracy by refining the Python bridge, switching device key lookup to strict equality, and ensuring correct handling of aliased kernel names in submodules. Utilized C++, Python, and CUDA, focusing on debugging, software optimization, and quantum computing to deliver robust and maintainable solutions within the codebase.