Worked on the SpikeInterface/spikeinterface repository to enhance the robustness of Kilosort sorting data aggregation workflows. Addressed a recurring issue where minor floating-point differences in sampling rates caused aggregation crashes by implementing a tolerance-based comparison using Python’s math.isclose function. This backend development effort improved the reliability and reproducibility of spike-sorting analyses by preventing unnecessary failures during data processing. The solution focused on floating-point tolerance handling and seamless Kilosort integration, resulting in reduced downtime for aggregation pipelines. Leveraging skills in backend development, data processing, and signal processing, the work strengthened confidence in automated data workflows without introducing new features.