Design a system to run LLM inference over a billion documents offline, as cheaply as possible.
Batch scoring a billion items is a throughput-and-cost problem, the reverse of low-latency serving. Every choice that harms latency works in your favor here. Here is how to design for dollars-per-million-documents.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Batch scoring a billion items is a throughput-and-cost problem, the reverse of low-latency serving. Every choice that harms latency works in your favor here. Here is how to design for dollars-per-million-documents.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
