Machine Learning & AI / Independent exploration
Resume–JD Semantic Matcher
A compact semantic retrieval API using normalized embeddings and inner-product search.
Problem
The project explores ranking résumé text against a job-description query.
Implementation
The inspected matcher creates a 384-dimensional FAISS IndexFlatIP, normalizes document and query vectors, and returns nearest-neighbor scores and identifiers.
Results
VERIFIED by source inspection: normalized inner-product retrieval is implemented. Ranking quality and hiring validity have not been established.
Limitations
Similarity is not evidence of job performance or candidate suitability. Document privacy, retrieval evaluation, and input handling remain deployment considerations.
Reproducibility
Reviewed at commit b268ee2fcb7d on 2026-11-09. Source inspection establishes implementation structure; repository-authored results are not independent measurements. The upstream application and benchmark suite were not rerun during this review.