Daniel Kim

Daniel Kim is a senior AI infrastructure engineer at NVIDIA on the Global Compute Infrastructure team. He focuses on optimizing observability to provide deep and reliable insights through metrics, logs, and traces across GPU clusters spanning multiple CSPs for faster detection, diagnosis, and resolution of issues. Before NVIDIA, he built and scaled cloud-native platforms at UiPath, Omnitracs (SmartDrive), and SAP, spanning Kubernetes controllers, GitOps architecture, CI/CD standardization, and production reliability across on-prem and cloud environments. He holds an MS in Computer Science from Georgia Tech and a BS from UC San Diego.
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Posts by Daniel Kim

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Networking / Communications May 07, 2026

Real-Time Performance Monitoring and Faster Debugging with NCCL Inspector and Prometheus

Distributed deep learning depends on fast, reliable GPU-to-GPU communication using the NVIDIA Collective Communication Library (NCCL). When training slows down,... 7 MIN READ