Worked on enhancing the numerical robustness of core linear algebra routines in the ignaciosica/tinygrad repository, focusing on stability improvements for SVD and QR computations. Addressed issues where NaN values could arise from zero or orthogonal inputs by refining algorithmic handling and adjusting tensor operations to prevent propagation of invalid values. Expanded unit testing to cover critical edge cases, ensuring reliable behavior in production workloads. Utilized Python and applied expertise in algorithm optimization, linear algebra, and numerical methods to deliver targeted bug fixes, including corrections to the SVD rank-1 Jacobi rotation logic when specific mathematical conditions, such as tau equaling zero, occurred.