Professional Machine Learning Engineer

The workload is input-bound: data extraction, transformation, and network loading occur before each TPU training interval, leaving the TPU idle while it waits for the next batch. Parallel file reads and preprocessing, together with prefetching, overlap input preparation with training and keep the TPU supplied with data without requiring more expensive accelerator hardware. Google Cloud recommends parallel reads, parallel map() calls, and prefetch() to mitigate TPU input-processing bottlenecks.