Matching candidates to jobs sounds simple until you try to do it well. Skills matching is table stakes — the real challenge is understanding context, potential, and culture fit.
Beyond Keyword Matching
Our first iteration used simple keyword matching on skills. It was fast but produced mediocre results. A "React developer" and a "React Native developer" are very different roles, but keyword matching treats them as nearly identical.
The Embedding Approach
We moved to embedding-based similarity search, converting job descriptions and candidate profiles into high-dimensional vectors. This captured semantic meaning — understanding that "team lead" and "engineering manager" are related concepts.