Research Scientist, AI Networking (PhD)

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Description

In this role, you will be a member of the AI Networking Software team and part of the bigger DC networking organization. The team develops and owns the software stack around NCCL (NVIDIA Collective Communications Library), which enables multi-GPU and multi-node data communication through HPC-style collectives. NCCL has been integrated into PyTorch and is on the critical path of multi-GPU distributed training. In other words, nearly every distributed GPU-based ML workload in Meta Production goes through the SW stack the team owns. At the high level, the team aims to enable Meta-wide ML products and innovations to leverage our large-scale GPU training and inference fleet through an observable, reliable and high-performance distributed AI/GPU communication stack. g. Large-Scale GenAI/LLM training) from the trainer down to the inter-GPU and network communication layer. We are seeking engineers to work on the space of GenAI/LLM scaling reliability and performance. Enabling reliable and highly scalable distributed ML training on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling

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