Attributed metadata history
Up to 100 retained publisher events per page for ab3a6a507ee03786effbfbc985d26964e032274b56863b53697d1a9b8a0e713c. Withdrawals and unavailable references remain attributed to their publishers.
intelligence_src_6dc544294b7f21f98a
observed · 2026-10-14 11:03:02 UTC
`# NeuroJob AI: LLM-Driven Candidate-Job Fit & Automated ATS Keyword Optimization Architecture Author: Lakshya Kurup Published: January 2026 | Repository: GitHub Abstract Job applicants frequently face high rejection rates due to non-standardized resume formats and sub-optimal Applicant Tracking System (ATS) keyword alignment. Traditional keyword matchers rely on static exact-string matching, missing semantic equivalents, context-aware experience mapping, and tailored interview preparation. NeuroJob AI addresses these challenges by implementing an end-to-end recruitment assistant powered by the Gemini API, Next.js, TypeScript, and Python. The platform provides automated resume-to-job description fit scoring, tailored cover letter synthesis, ATS keyword gap analysis, and predictive interview question generation within a single, highly responsive interface. 1. System Architecture & Tech Stack The system is built on a modular client-server architecture designed for low-latency prompt execution and structured schema outputs: Component Technology Role Frontend Next.js (App Router), React, TypeScript, Tailwind CSS Dynamic user dashboard, AT
Fingerprint: 72824d90e70ca500dee02f915edf9b8482cb6aaa9b143dbbadbdce3b7fd21eb9
intelligence_src_6dc544294b7f21f98a
observed · 2026-10-12 11:01:03 UTC
available
Fingerprint: 2faf9469031bd0e00603457ab86d15e2040aea06ef98482184945872c5cb389f