PetProject: Automated Candidate Search & Analysis System I am currently developing an advanced system designed to streamline the hiring process by automating candidate searches across multiple platforms. This system leverages a robust automated search mechanism that scans portfolios using specific keywords.

The system integrates a Large Language Model (LLM) to parse and analyze candidate details, offering a comprehensive understanding of each candidate's qualifications. Users can input a description of the ideal candidate, and the LLM will assign a ranking score from 0 to 100, indicating the candidate's suitability for the position.

In addition to candidate matching, the system provides detailed analytics, including the average age, locations, salary expectations, and experience levels of the identified candidates. This project is aimed at simplifying and enhancing the recruitment process, making it easier for users to find the best fit for their job openings.