One GPU, callers blocking on the response, and a hardware unit that is only efficient when fed wide batches. The whole job is trading a few milliseconds of queue wait for a large jump in throughput without ever stalling a request.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
One GPU, callers blocking on the response, and a hardware unit that is only efficient when fed wide batches. The whole job is trading a few milliseconds of queue wait for a large jump in throughput without ever stalling a request.
The senior signal is naming the three knobs that define a batcher: max batch size, max wait time, and an early-flush on queue depth, then reasoning about the latency/throughput tradeoff between them with numbers. Strong candidates raise padding waste and length bucketing unprompted, and they isolate per-item failures so one bad input cannot fail the whole batch. The reserve follow-up is almost always 'now you have 8 GPUs', which tests whether they reach for continuous batching and a load balancer keyed on queue depth rather than round-robin. Watch for candidates who batch but never bound the queue, so a traffic spike turns into unbounded latency instead of backpressure.
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