JobGennie

A job hunt is a dozen tabs at once: scanning several boards, second-guessing whether a résumé will survive the ATS filter, rewriting it for every posting, and losing track of who you applied to and when. Every part of that is doable by hand and none of it is worth doing by hand.

JobGennie collapses a scattered job search into one platform. You maintain a single profile — skills, experience, education — and it aggregates openings from multiple boards, scores each against you with a fit score, evaluates your résumé the way an Applicant Tracking System would, generates a tailored résumé for a specific role, and tracks every application through its full lifecycle.

Three services around one MongoDB store. A Node/Express API owns accounts, jobs and the application pipeline; a Python service does the thinking — TF-IDF and cosine similarity for fit scoring, keyword and section analysis for ATS, and templating (never generation) for tailored résumés, so nothing is invented; React drives the dashboard. It is a Semester 4 academic project and deliberately classical ML — no LLMs, no vector database — which keeps every score explainable.