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JobLink

A comprehensive job recommendation and hiring platform designed to connect job seekers with relevant opportunities and empower companies with intelligent recruiting tools.

Repository: github.com/IRIvey/JobLink


Table of Contents


Overview

JobLink is a full-stack web application that bridges the gap between job seekers and employers. The platform leverages skill-based matching, AI-powered candidate evaluation, and real-time analytics to streamline the hiring process for both sides.

The application features:

  • Role-based profiles for job seekers and companies
  • Intelligent job recommendations based on skill matching
  • Comprehensive application management system
  • AI-assisted candidate evaluation and summarization
  • Real-time hiring analytics and insights
  • Professional resume builder with PDF export

Problem Statement

Current Challenges

  1. Job Seekers: Difficulty finding opportunities that match their specific skills and qualifications
  2. Companies: High volume of irrelevant applications, consuming valuable recruiting resources
  3. Resume Creation: Manual CV creation is time-consuming and inconsistent
  4. Communication: Inefficient, fragmented communication throughout the hiring pipeline

JobLink's Solution

JobLink addresses these pain points through:

  • Automated skill-based job matching to connect qualified candidates with relevant positions
  • Streamlined application workflows that reduce irrelevant submissions
  • Integrated resume builder for fast, professional CV creation
  • Centralized communication and application management within a single platform

Key Features

For Job Seekers

Feature Description
Dashboard Track applied jobs, monitor application statuses, and view personalized recommendations
Profile Management Build comprehensive profiles including skills, education, and work experience
Smart Job Search Discover jobs with fuzzy search and skill-based recommendations
Resume Builder Create professional CVs with tailored templates and download as PDF
Application Tracking Monitor real-time status updates (Applied, Shortlisted, Rejected, Selected)

For Companies

Feature Description
Dashboard Monitor active job posts, applicant counts, and hiring progress at a glance
Job Posting Create and publish job listings with specific skill requirements
Applicant Management View, shortlist, reject, and select candidates per job post
AI Application Summary Receive AI-generated candidate summaries to accelerate evaluation
Analytics & Insights Access real-time hiring statistics, match scores, and recruitment trends

Cross-Platform

Feature Description
Role-Based Access Control Separate, secure login flows for job seekers and companies
Responsive Design Seamless experience across desktop and mobile devices

Tech Stack

Backend

  • Runtime: Node.js
  • Framework: Express.js
  • Authentication: bcrypt.js (password hashing)
  • Database: MongoDB

Frontend

  • Framework: React.js
  • Languages: HTML5, CSS3, JavaScript (ES6+)
  • Additional Tools: React components for UI, resume PDF generation library

DevOps & Tools

  • Containerization: Docker
  • Version Control: Git and GitHub
  • Development Environment: VS Code

Installation & Setup

Prerequisites

  • Node.js (v14 or higher)
  • npm or yarn
  • MongoDB instance (local or cloud-based)
  • Git

Backend Setup

# Clone the repository
git clone https://github.com/IRIvey/JobLink.git
cd JobLink

# Install backend dependencies
npm install

# Configure environment variables
# Create a .env file with the following:
PORT=5000
MONGODB_URI=<your-mongodb-connection-string>
JWT_SECRET=<your-jwt-secret>
BCRYPT_ROUNDS=10

# Start the backend server
npm start

Frontend Setup

# Navigate to the frontend directory
cd client

# Install frontend dependencies
npm install

# Configure API endpoint
# Update the API base URL in your React configuration

# Start the development server
npm start

The application will be available at http://localhost:3000

Docker Setup (Optional)

# Build and run with Docker
docker-compose up --build

Project Architecture

Database Schema

JobLink uses MongoDB with the following primary collections:

  • Users – Job seekers and companies with authentication details
  • Jobs – Job postings with required skills and descriptions
  • Applications – Application records with status tracking
  • Profiles – Extended user profiles (education, experience, skills)
  • Resumes – Saved resume data for PDF generation
  • Analytics – Aggregated hiring metrics and statistics

Key Workflows

Job Seeker Flow:

Profile Creation → Skill Definition → Job Search → Apply → Track Status

Company Flow:

Company Profile → Job Posting → Review Applications → AI Summary → Shortlist → Hire

Recommendation System:

  • Analyzes job seeker skills against job requirements
  • Ranks jobs by match score
  • Surfaces top recommendations in the dashboard

Future Enhancements

Short Term

  • Advanced Candidate Ranking: Extend AI summaries to automatically score applicants based on job requirements
  • Real-Time Chat: Implement in-app messaging between companies and applicants
  • Interview Scheduling: Add calendar integration with automated reminders

Medium Term

  • ML-Powered Recommendations: Enhance matching algorithm by learning from user behavior patterns
  • External Job Board Integration: Aggregate listings from popular job platforms to expand opportunities
  • Email Notifications: Automated alerts for application updates and new matching jobs

Long Term

  • Video Interview Integration: Built-in video interview tools and recordings
  • Skill Assessment Platform: Incorporate technical assessments and coding challenges
  • Enterprise Features: Role-based access control, team management, and custom workflows

Contributing

Contributions are welcome! Please follow these guidelines:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/YourFeature)
  3. Commit your changes (git commit -m 'Add YourFeature')
  4. Push to the branch (git push origin feature/YourFeature)
  5. Open a Pull Request

Project Information

  • Academic Supervisor: Jibon Naher, Lecturer, CSE
  • Industrial Supervisor: Maheen Mashrur Haque
  • Application Domain: Recruitment and HR systems, Job marketplace platforms, Skill-based matching
  • Status: Completed DP-I Project

License

This project is part of an academic curriculum at the Department of Computer Science and Engineering.


Contact & Support

For issues, feature requests, or questions, please open an issue on the GitHub repository.


Last Updated: April 2026 | Version: 1.0

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