Ali Ganjei is an Enterprise Systems Engineer with 11 years of experience designing and operating large-scale Linux and GPU-accelerated compute platforms for performance-critical workloads. He has led HPC and AI cluster architecture and delivery—covering RDMA networks (InfiniBand, RoCE), NVIDIA DGX/HGX systems, and Slurm/Kubernetes scheduling—while marrying datacenter constraints with workload-driven hardware selection. His deep Linux kernel and networking expertise informs system-level optimizations for high throughput and low latency, and he prioritizes reliability through observability, failure analysis, and automation. At Meta he partners with Reality Labs Research to turn complex research requirements into production-ready infrastructure and builds Python tooling to simplify low-level operational tasks. Comfortable across cloud, on-prem, and hybrid environments, he specializes in bridging research needs with long-term operationalization of cutting-edge compute. Colleagues rely on him to translate nuanced performance trade-offs into pragmatic, scalable architectures.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BS) Computer Hardware Engineering, Bachelor of Science (BS) Computer Hardware Engineering at Sharif University of Technology
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