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Intelligent resume parsing platform that extracts structured data and matches candidates with perfect job opportunities
Build a sophisticated resume parsing platform that uses NLP to extract skills, experience, education, and achievements from resumes in any format. Implements advanced entity recognition, skill gap analysis, and semantic job matching. Features real-time resume feedback, ATS compatibility scoring, and personalized career path recommendations. Includes bulk processing API for recruitment agencies and integration with major job boards.
Multi-format resume parsing
Skill extraction and normalization
Experience timeline generation
ATS compatibility scoring
Semantic job matching
Skill gap analysis
Career path recommendations
Bulk processing API
Real-time resume feedback
Job board integration
Next.js frontend with server components, Python FastAPI microservices, pgvector for semantic search, Celery for async resume processing, Redis for caching, and Elasticsearch for job matching
NLP/Transformers
Next.js 14
Python/FastAPI
Vector databases
Full-stack development
Job recruitment domain
Master document parsing
Implement semantic search
Build recommendation systems
Handle multiple file formats
Deploy ML models
Design recruitment workflows
System design and database schema
PDF/DOCX parsing pipeline
Fine-tune SpaCy for resume entities
pgvector semantic matching
Next.js resume upload and editor
Semantic job-candidate matching
ATS compatibility algorithm
Career recommendation engine
Bulk processing REST API
Performance and accuracy tuning