Worked on the llm-d/llm-d-benchmark repository, focusing on improving system reliability and configuration accuracy. Addressed a critical issue by correcting a typographical error in the inference-perf configuration path, ensuring that both continuous integration and local experiments could reliably locate and load the necessary configuration directory. This change reduced misconfiguration failures and improved the reproducibility of benchmark runs. The work involved careful attention to Python code and configuration file management, emphasizing maintainability and stability over new feature development. By resolving this bug, the developer accelerated troubleshooting and enabled more consistent performance insights for the benchmarking workflow during the project period.