The AI-Powered Resume Screen System is an intelligent recruitment support platform designed to automate, simplify, and enhance the employee hiring process. Traditional recruitment involves manually reading and evaluating large volumes of resumes, which is not only time-consuming but also prone to human error and subjective judgment. This project aims to overcome these challenges by integrating machine learning, structured data processing, and a role-based workflow system that benefits candidates, recruiters, and administrators.
The system allows candidates to register, maintain profiles, upload resumes, and apply for relevant job openings. Recruiters can post job vacancies, manage applicant details, and review machine-generated skill matches and similarity scores that help them identify the best-suited candidates. A machine learning component performs resume text extraction, TF-IDF similarity scoring, and skill keyword matching, enabling more accurate and unbiased preliminary screening. The system identifies how closely an applicant’s resume aligns with job requirements, helping recruiters make informed decisions quickly.
Key Features
1. Automated Resume Screening (ML-Based)
- The system extracts text from uploaded resumes (PDF/DOCX).
- Machine Learning assigns a score based on skill matching, keywords, and job relevance.
- Reduces manual effort and speeds up shortlisting.
2. Role-Based Access Control
- Recruiter: Posts jobs, views applicants, updates application status, checks ML results.
- Candidate: Applies for jobs, uploads resumes, views application status and history.
3. Job Posting with Rich Text Editor
- Recruiters can post detailed job descriptions using CKEditor (fonts, colors, formatting).
- Application deadlines ensure expired jobs are automatically marked as closed.
4. Intelligent Application Tracking
- Candidates see their applied jobs, ML scores, matched skills, and recruitment status.
- Recruiters can change the status of applications (Pending / Accepted / Rejected).
- Complete application history is stored for future reference.
5. Deadline-Based Job Validation
- If the application deadline is passed, the system automatically:
- Marks the job as expired,
- Prevents new applications,
- Displays a proper “Closed” badge.
6. Real-Time Notifications & Messages
- The system uses Django messages to show success/error notifications.
- Candidates and recruiters get feedback after every action.
7. Secure User Authentication
- Login system with custom password reset.
- Session-based secure login for candidates and recruiters.
8. Modern & Responsive UI
- Full TailwindCSS-based frontend for a clean and professional design.
- Works smoothly on mobile, laptop, and desktop.
This project is ideal for BCA, MCA, B.Tech, BE, M.Tech, and final-year students who want to work on a real-world Machine Learning application with practical use cases in the HR domain.
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