Worked on improving reliability and correctness in neuralmagic’s compressed-tensors and guidellm repositories by focusing on backend development and data validation using Python. Addressed two critical bugs, including implementing dimension validation for QuantizationArgs block structures to ensure only positive integers are accepted, with comprehensive unit tests to catch invalid inputs. In guidellm, fixed the safe_add function so that the first accumulator value correctly respects the intended sign, supported by regression tests. Enhanced overall code quality by expanding unit test coverage, integrating static analysis tools like mypy and ruff, and maintaining CI hygiene to minimize production risk in machine learning pipelines.