AI-Powered Job Matching Application Using ERNIE SDK

This project, contributed by Gao Fuzhi (PaddlePaddle developer expert, community leader, and entrepreneur), focuses on AI-native application development using large language models. It builds an AI-driven job matching workflow with the ERNIE SDK to achieve precise matching between talent and positions.

Current job seekers face many challenges: existing recruitment platforms only provide basic posting and search functions, making it difficult to achieve accurate and efficient matching. Job seekers waste time filtering information with uncertain results, while platforms struggle to expand into new markets, especially for low‑ and mid‑level recruitment. AI job‑matching applications aim to solve these problems by leveraging intelligent technologies for precise position targeting, benefiting both candidates and employers.

The application uses the ERNIE SDK to intelligently analyze a user's resume or personal profile, accurately match the most suitable positions and companies, and provide detailed suggestions such as salary range, location, benefits, and requirements.

Feature 1: AI Job Matching

Job seekers input their employment needs and resume data; the AI model performs deep analysis to determine the most suitable positions. An agent then filters companies hiring for those positions and returns company name, job title, salary range, location, and detailed job benefits and requirements.

The matching logic consists of four steps:

User inputs resume; the system fills a built‑in Prompt and sends it to the large model, selecting an appropriate model based on input length.

The model parses the input and outputs a JSON with fields such as city, position, and salary.

These fields are used to query a recruitment database (local or external) for preliminary matches.

Based on the preliminary data, the system retrieves detailed job requirements, combines them with the user's profile in a Prompt, and queries the model again to produce a refined match.

Feature 2: AI Job Analysis

The application leverages the ERNIE model to deeply analyze the requirements of target positions, extracting skill demands, ability requirements, and changes in job needs. Users can select a company of interest and receive a structured summary of the job requirements.

Feature 3: Personal Information Analysis

The agent considers both the job requirements and the candidate’s background (education, experience, skills) to provide a comprehensive personal analysis, highlighting competitive advantages, skill‑improvement directions, and interview preparation suggestions.

The project concludes that the ERNIE SDK enables an efficient AI job‑matching system with three core functions: AI job matching, AI job analysis, and personal information analysis. The source code is not extensively shown, but the workflow is detailed.

Application demo link: https://aistudio.baidu.com/application/detail/30228

Future updates may include using ERNIE‑UIE for information extraction, adding PDF/Word resume upload, and developing additional features such as AI mock interviews and interview question generation.