Worked on the vllm-project/vllm-ascend repository to deliver reliability and performance improvements for vLLM-Ascend integration. Addressed a critical tensor size compatibility issue in the model runner, resolving runtime errors between fc1 and non-single-padding configurations. Optimized DeepSeekOCR2 model components, specifically RelPosAttention and CustomQwen2Decoder, to accelerate OCR inference and reduce latency. Enhanced the project’s documentation to support deployment and evaluation, improving onboarding for developers. Collaborated across teams to validate changes against the vLLM baseline, ensuring consistency and stability. Leveraged deep learning, model optimization, and Python expertise to deliver robust solutions in machine learning and natural language processing workflows.