During September 2025, Avavre focused on improving the correctness and stability of FP8 mixed-precision workflows in the NVIDIA-NeMo/Megatron-Bridge repository. Avavre delivered a targeted bug fix for the MXFP8 recipe, enforcing E4M3 FP8 precision across both BF16 and FP16 mixed-precision training. This involved updating configuration files to standardize the FP8 format and expanding unit tests to validate the new precision settings. Working primarily in Python and leveraging deep learning and model optimization expertise, Avavre’s work addressed precision drift and training instability, resulting in more reproducible and stable large-scale model training within the Megatron-Bridge pipeline.