Smart Resume Matcher · NLP
Matching resumes to jobs with the precision of a search engine.
Core Concept
Parses resumes and instantly matches them to job postings using TF-IDF, Word2Vec, and Sentence-BERT embeddings with FAISS for sub-second vector search and weighted cosine scoring.
Role
Developer
Stack
Python / Flask
React.js
Scope
NLP
Machine Learning
Repo
GitHub
Key Features
01
Resume parsing
Extracts skills, experience, and education from PDF/DOCX resumes using spaCy and NLTK pipelines.
02
Multi-model matching
TF-IDF, Word2Vec, and Sentence-BERT embeddings combine for richer, more accurate job matching.
03
FAISS vector search
Sub-second similarity queries across indexed job descriptions using weighted cosine scoring.
04
Match insights
Clear, real-time match breakdowns for candidates and recruiters, not just a score, but why.
Technologies
A full NLP pipeline from ingestion to insight.
Python 3.9+
Flask / FastAPI
spaCy + NLTK
NLP pipeline
Sentence-Transformers
all-mpnet-base-v2
FAISS
Vector search
MongoDB
Parsed data & embeddings
React.js + MUI
Frontend dashboard
Contributors
Demo