RAG Interview Questions, issue 1, Jul 5, 2026
The Averaging Trap
Senior ML Engineer interview at Google, and the interviewer asks:
“You’ve got three retrievers, BM25, a dense embedding model, and a rerank pass, and their relevance scores live on completely different scales. How do you merge them into one ranked list?”
Don’t say: “Just average the scores.”
Why naively blending BM25 and dense scores quietly lets one retriever steamroll your relevance, and the rank-based trick that saves your hybrid search from magnitude outliers.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.