Jobpin AI项目 中期Demo展示 | 23期全栈项目 | 澳洲IT

The Jobpin AI project is an AI-driven job search platform that aims to optimize the job search process and improve competitiveness by intelligently matching user resumes with positions, personalized job recommendation, and providing resume optimization tools. The platform collects and organizes job data from multiple channels and uses large language models for parsing and standardization. The core architecture uses Resume-Graph (RG) technology to achieve accurate matching and improve job search efficiency through compatibility scoring. In addition, the AI ​​dynamic resume customization tool optimizes resume content according to job requirements. The team has completed key functions such as homepage, user authentication and guidance process, job list, resume editor, and job and resume parsing modules. The platform is based on SEO, accessibility, and performance optimization, with AWS Lambda used for data management on the backend and Redux used for state management on the front end. Future plans include optimizing resume generation, enhancing job matching algorithms, and integrating Stripe for payment processing. The team believes that the job search process is similar to endlessly searching for content on Netflix, and many positions are not suitable, wasting a lot of time. They attach great importance to data management and privacy security, and plan to conduct small-scale tests to optimize system stability and user experience. The team is confident in the scalability of the platform and plans to work directly with employers to provide exclusive job information. User feedback and system flexibility are one of the core values ​​of the project, especially in the resume creation and matching process, ensuring that users can adjust and optimize their profiles at any time. The team will continue to improve and focus on improving the resume editor and matching algorithm to provide more accurate and efficient job search services. Jobpin AI 项目是一个 AI 驱动的求职平台，旨在优化求职流程，通过智能匹配用户简历与职位、个性化推荐工作机会，并提供简历优化工具来提升竞争力。该平台收集和整理多个渠道的职位数据，并利用大语言模型进行解析和标准化。核心架构采用 Resume-Graph (RG) 技术，实现精准匹配，并通过兼容性评分提高求职效率。此外，AI 动态简历定制工具可根据职位需求优化简历内容。团队已完成关键功能，如首页、用户认证和引导流程、职位列表、简历编辑器，以及职位和简历解析模块。平台基于 SEO、可访问性和性能优化，后端使用 AWS Lambda 进行数据管理，前端采用 Redux 进行状态管理。未来计划包括优化简历生成、增强职位匹配算法，并集成 Stripe 进行支付处理。 团队认为，求职过程类似于在 Netflix 上无休止地翻找内容，很多职位并不合适，浪费了大量时间。他们高度重视数据管理和隐私安全，并计划进行小规模测试，以优化系统稳定性和用户体验。团队对平台的可扩展性充满信心，并计划与雇主直接合作，提供独家职位信息。用户反馈和系统灵活性是项目的核心价值之一，尤其是在简历创建和匹配过程中，确保用户能够随时调整和优化个人资料。团队将持续改进，专注于提升简历编辑器和匹配算法，以提供更精准和高效的求职服务。