AI/ML

Resume Matcher – AI-Powered ATS

The AI-Powered ATS helps bridge the gap between job seekers and recruiters. By using advanced NLP, it doesn't just look for keywords; it understands the context of skills and experience to match candidates with the most relevant job descriptions.

Project typeIndependent build
StatusCompleted project
FocusAI/ML

Technology

PythonNLPScikit-learnFlaskspaCy

System approach

  • Parsing: spaCy and PyPDF2 for structured data extraction.
  • NLP: Word2Vec and Cosine Similarity for semantic matching.
  • Backend: Flask-based API for handling resume uploads and processing.

Challenges

  • Handling various resume formats (PDF, DOCX, Images).
  • Understanding semantic similarity (e.g., 'React Developer' matching 'Frontend Engineer').
  • Ensuring fair and unbiased scoring.

Solutions

  • Standardized all input formats into a clean text representation using robust OCR and parsing libraries.
  • Utilized pre-trained word embeddings to capture semantic relationships between different job titles.
  • Implemented a transparent scoring breakdown that highlights matching skills and missing gaps.

Key outcomes

01

NLP-powered matching

02

ATS compatibility scoring

03

Recruiter workflow optimization