Resume Parsing

Resume parsing is the automated extraction of structured candidate data from resume files. A parser converts a PDF, Word document or image into named fields — contact details, work history, education, skills — that software can store, search and rank.

In one paragraph

Parsing sits at the front of every recruiting pipeline: nothing downstream — search, matching, screening, analytics — can operate on an unparsed document. Modern parsers use large language models over a five-stage pipeline (ingestion, OCR, layout reconstruction, extraction, normalization) and return a deterministic schema of 50+ fields regardless of the document's layout or language.

Example

A candidate uploads resume.pdf; the parser returns {"candidate_name": "Linda Harris", "positions": [{"position_name": "Test Engineer", "skills": ["Agile", …]}], …} — a real payload is explorable at resume to JSON.

Go deeper

The full treatment: what is resume parsing · how it works, stage by stage · the SharpAPI implementation .