Worked on the NVIDIA/KAI-Scheduler project, focusing on enhancing the correctness and reliability of resource scheduling in a Kubernetes-based backend environment. Addressed a critical bug by refining the scheduler’s resource enumeration logic to exclude resources with a count of zero, thereby improving allocation accuracy and reducing resource waste. This targeted change, implemented in Go, ensured more feasible scheduling plans and better resource utilization across workloads. The work emphasized careful debugging, code hygiene, and low-risk change management, maintaining production stability while laying the groundwork for future optimizations. No new features were shipped, with efforts concentrated on reliability and backend robustness.