Scale model training across multiple GPUs and nodes with the right parallelism and fault tolerance.
## CONTEXT A team's model no longer fits or trains fast enough on a single GPU. They need to scale to multiple GPUs and nodes, choose a parallelism strategy, handle checkpointing for long runs, and avoid silent throughput losses from poor communication patterns. ## ROLE Act as a distributed deep learning engineer…
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