AI-Driven Recruitment Platform Development

We are seeking a developer or development team to create a cutting-edge recruitment platform that not only matches job descriptions with candidate CVs using AI but also automatically extracts key information from CVs to populate user profiles. Here are the detailed requirements: **Key Features:** 1. **User Registration & Profiles:** - **Recruiters:** - Registration with company details, job roles, and contact information. - Dashboard to post job descriptions (JDs) and view AI-matched CVs. - **Job Seekers:** - Profile creation where the platform reads, parses, and populates information from uploaded CVs. - Manual editing options for all auto-populated data to ensure accuracy and completeness. - Control over CV visibility settings (public, semi-private, private). 2. **Automatic CV Parsing:** - Upon CV upload, the system should: - Extract contact information, work experience, education, skills, certifications, etc. - Automatically populate the job seeker's profile with this data. - Provide an intuitive interface for job seekers to review and correct the parsed information. 3. **AI-Driven Job Matching:** - Use AI/ML algorithms to analyze JDs and match them with parsed CV data based on skills, experience, and keywords. - Continuous learning to improve matching accuracy over time. 4. **Job Posting System:** - Recruiters can post job descriptions with specific qualifications, skills, and roles. - System suggests CVs based on AI matches. 5. **CV Management:** - Secure storage for CVs with encryption for data protection. - Version control for CV updates by job seekers. - Recruiters can download or view CVs based on AI matches. 6. **Search and Filtering:** - Advanced search options for recruiters enhanced by AI suggestions on parsed CV data. - Job seekers can search for jobs with AI-enhanced recommendations. 7. **CV Boosting:** - Feature for job seekers to pay for boosting their CV, making it appear higher in search results or AI matches for a specified period. 8. **Privacy and Security:** - Implement stringent security measures to protect personal data. - GDPR compliance and other relevant data protection regulations. 9. **Payment Gateway Integration:** - For subscriptions or one-time payments: - Recruiters: Monthly/yearly subscriptions, pay-per-CV, or flat fee for CV access. - Job Seekers: Premium profile features, CV boosts, or one-time access fees. - Secure payment processing (Stripe, PayPal, etc.). 10. **Analytics and Reporting:** - Recruiters can track how many CVs were viewed, downloaded, and feedback on applications. - Job seekers get insights on job applications, profile views, and CV boost effectiveness. 11. **Communication Tools:** - In-app messaging system for direct communication between recruiters and candidates. 12. **User Experience:** - Responsive design for mobile and desktop. - Intuitive UI/UX to ensure ease of use for both employers and job seekers, especially for the CV parsing and editing process. 13. **Scalability & Performance:** - Designed to handle high traffic and large data sets without performance degradation. **Technical Requirements:** - Backend: Node.js, Python (Django or Flask), or similar, with AI/ML capabilities for CV parsing (TensorFlow, PyTorch, NLP libraries like NLTK or spaCy, etc.). - Frontend: React.js, Vue.js, or Angular. - Database: PostgreSQL, MongoDB, or MySQL for storing parsed data. - Cloud Services for hosting, scalability, AI processing, and potentially OCR for CV scanning if needed (AWS, Google Cloud, etc.). - RESTful API for potential integrations or future expansions. **Deliverables:** - A fully functional MVP with core features including AI matching, CV parsing, and CV boosting. - Documentation for setup, API usage, system administration, and AI model management. - User manuals for both recruiter and job seeker interfaces, with detailed instructions on CV parsing and profile editing. **Additional Notes:** - Please provide examples of similar projects you've worked on, especially those involving AI/ML and document parsing. - We're open to discussing project phases if the entire scope is too broad for one initial launch. - The CV parsing feature should be accurate yet allow for easy manual correction by the job seeker. **How to Apply:** - Include your portfolio, particularly projects relating to web platforms, recruitment tools, AI applications, or document parsing. - Estimate the timeline and cost for the project based on the features described. - Specify your approach to security, data privacy, scalability, AI integration, and how you plan to handle CV parsing.