AI Resume Screener
Talent-Match is an AI-powered resume screener that reads between the lines. It doesn't just keyword-match "Python" and call it a day—it understands context.
💡 The Problem with Traditional ATS
Applicant Tracking Systems fail when a candidate says "built scalable microservices" instead of using the exact phrase "Spring Boot REST API". Humans get it. Old systems don't.
🤖 How It Works (Under the Hood)
- Document parsing: Extract text from PDFs/DOCX using Mammoth.js (preserves formatting context like bold headers)
- Semantic embedding: Convert resume + job description into vector embeddings using OpenAI's
text-embedding-3-largemodel - Cosine similarity: Calculate match score (0-100%) based on vector distance—"experienced in distributed systems" matches "built Kafka pipelines" even without shared keywords
- Explainability: GPT-4 generates human-readable reasoning: "Candidate's experience with Docker/K8s aligns with DevOps requirement"
✨ Smart Features
- Skill inference: "Led team of 5 engineers" → automatically tags [Leadership, Team Management]
- Experience weighting: Recent roles scored higher than 10-year-old internships
- Red flag detection: Employment gaps, frequent job hopping, mismatched education—flagged for human review
- Batch processing: Screen 100 resumes in 2 minutes vs. 2 hours manual review
🎯 Real-world impact: Reduced time-to-hire by 40% in pilot test with 500+ applicants for 3 engineering roles.
🔮 Technical Stack
| Frontend | React + TypeScript (drag-and-drop resume upload with progress bars) |
| Backend | Node.js Express + OpenAI API (streaming responses for real-time feedback) |
| NLP Pipeline | Custom prompt engineering with few-shot examples for consistency |
Best use case: High-volume hiring for technical roles where skill depth matters more than keyword density
- StackJavaScript, NLP, OpenAI API
- Sourcehttps://github.com/Shorya-agarwal/Talent-match
