Intel / article

Semantic Search For Ai Agents At Scale Retrieval And Ranking For Linkedins Hiring Assistant

Terms in this piece · Glossary

eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
embedding — A list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
LLM-as-judge — Using one model to score another's output against a rubric, so quality can be measured at a scale human grading cannot reach.

Why it matters

Semantic retrieval for an needs a scoring rubric before it needs a model: LinkedIn defined "qualified", built an to that standard, then trained on those judgments to rank 1.3B profiles in real time.