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Prachi
Prachi

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ApplyMate: An AI-Powered Job Application Assistant 🚀

#devchallenge #hf26challenge

Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Submission 🦥

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

What I Built

Searching for a job in tech can feel like an exhausting numbers game. Job seekers apply to dozens of positions, struggle to understand applicant tracking systems (ATS), spend hours tailoring resumes and cover letters, and lose track of applications and follow-ups across spreadsheets.

We built ApplyMate — AI Job Application Assistant, an open-source career management platform designed to make the job search more organized, transparent, and accessible.

Our goal is to bring essential job-search tools together in one place and help candidates manage their resumes, organize job opportunities, and present their skills more effectively.

The Slow and Steady Approach

ApplyMate helps reduce repetitive work during the job search. Instead of manually reviewing every job description against a resume, candidates can use semantic matching to identify relevant experience and better understand how their skills align with job requirements.

Resume parsing, job organization, application tracking, and AI-assisted resume improvements help bring these tasks into one platform, saving effort and making the job search easier to manage.

Demo

GitHub Repository: https://github.com/AI-Teacher-Assistant/Apply_Mate

Code

https://github.com/AI-Teacher-Assistant/Apply_Mate?utm_source=chatgpt.com

How I Built It

Technologies Used: - Frontend: HTML5, CSS3

  • Backend: Node.js (v24), Express.js
  • Database: MongoDB, Mongoose
  • Resume Processing: Multer, pdf-parse
  • Security & Authentication: JSON Web Tokens (JWT), bcryptjs, Helmet, express-rate-limit
  • Testing: Node.js Native Test Runner, node:as sert, Supertest

Open-Source AI: Open-Weight Model: all-MiniLM-L6-v2
Open-Source AI Framework: Hugging Face Transformers.js (@xenova/transformers)
Inference Runtime: ONNX Runtime with WebAssembly
Optional LLMs: Llama 3.3 70B via Groq and Llama 3.2 3B via local Ollama.

We want to explore how open-source AI can make career tools more transparent, accessible, and useful.

Why Does Open Innovation Matter?

  1. Privacy and Control Over Career Data: Open-source tools can give developers greater control over how personal resume information is processed, especially when AI runs locally.

  2. Transparent Job-to-Skill Matching: Explainable matching can help job seekers understand how their skills align with job requirements instead of relying only on opaque scores.

  3. Accessible Career Tools: Open-source technologies can help reduce dependence on expensive services and make useful tools more accessible.

  4. Community-Driven Improvement: Open innovation encourages developers to share ideas, review code, contribute improvements, and learn together.

Team Submission:

ApplyMate is a collaborative project developed by the AI Teacher Assistant team. This submission represents our team's work, and we are publishing one post for the entire team.
Team members:

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