During September 2025, William Brown upgraded machine learning tooling in the coreweave/ml-containers repository to enhance performance and reproducibility across environments. He updated the vLLM tensorizer to version 0.10.2 and flashinfer to 0.3.1, integrating these changes with new workflow configuration files and Dockerfiles. This approach streamlined both local and CI deployments, ensuring consistent builds and improved reliability. William applied his expertise in DevOps, Python, and containerization to implement these updates, focusing on maintainable deployment scaffolding. The work addressed the need for up-to-date dependencies and robust deployment processes, demonstrating a solid understanding of modern ML infrastructure requirements.