Automated Job Screener NLP Engine is an intelligent system that leverages Natural Language Processing and vector search technology to match job candidates with relevant positions based on resume and job description analysis.
The system streamlines the recruitment process by automatically analyzing resumes and job descriptions, identifying relevant skills and qualifications, and ranking candidates for specific positions. It uses semantic understanding and vector embeddings to go beyond simple keyword matching.
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Sentence Transformers, Hugging Face Transformers, spaCy, scikit-learn -
FAISS, Qdrant, Vector Embeddings -
Python, LangChain, NLTK -
Streamlit, Streamlit Option Menu, Plotly, Altair
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- Multi-modal document support: Process resumes in various formats (PDF, DOCX, TXT, images with OCR)
- Automated information extraction: Extract skills, experience, education, and other key information
- Document summarization: Generate concise summaries of resumes and job descriptions
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- Hybrid search architecture: Combines semantic (vector) search with traditional keyword matching
- Skill-based matching: Maps candidate skills to job requirements with semantic understanding
- Customizable ranking: Adjust matching priorities based on different criteria
- User feedback loop: Continuously improve matching through feedback integration
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- Candidate pool analysis: Visualize skill distribution and candidate qualifications
- Gap analysis: Identify missing skills and suggest upskilling opportunities
- Market insights: Understand trends in job requirements and candidate qualifications
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- Automated interview question generation: Create relevant questions based on candidate profile and job requirements
- Custom knowledge graph: Visualize relationships between skills and requirements
- Multilingual support: Process documents in multiple languages
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git clone https://github.com/realshubhamraut/Automated-Job-Screener-NLP-Engine.git cd Automated-Job-Screener-NLP-Engine