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Design a Distributed Model Training Platform is a hard system design interview question covering Distributed Systems, machine learning, scheduling, deep learning, storage — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Design the platform that runs large model training jobs on a shared cluster of about 1,000 GPUs, 8 per node. It serves a mixed workload: a few flagship runs holding hundreds of GPUs for weeks, a constant stream of 1 to 64 GPU research jobs, and interactive sessions people expect to start in seconds. Something in the cluster fails every day or two, and a three-week run must finish unattended without losing more than an hour of progress to any single failure. The platform is judged on cluster allocation and on model FLOPs utilisation within jobs.
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