AI / MLCompleted System2024

CareerForge AI — Intelligent Career Guidance & Resume Analysis

Role: AI Systems Engineer

AI-driven career development platform parsing student resumes to match international tech roles and identify skill deficits.

Verified Project Links & Repositories

2 Active Resources

GitHub Repository (Main)

Primary verified codebase, implementation, and commit history

Technical Documentation

Architecture diagrams, API references, and setup guide

CareerForge AI — Intelligent Career Guidance & Resume Analysis

Technology Stack & Libraries

PythonFastAPISentence-TransformersFAISSNext.jsTailwind CSS

The Challenge / Problem

Context & Objectives

Undergraduates frequently submit generic resumes to international opportunities without knowing which technical keywords and competencies are missing.

Architectural Solution

Engineered Approach

Implemented dense vector embeddings to compare candidate project descriptions against target job specifications, highlighting high-leverage skill gaps.

System Architecture & Pipeline

PDF Upload -> PyMuPDF Parsing -> Sentence-Transformers Embedding -> Cosine Similarity Index -> Roadmap Generation LLM.

CareerForge AI bridges the information gap between university students and international technology internships. By analyzing uploaded PDF CVs against real-time job market requirements, the system computes match percentages and builds tailored 12-week upskilling paths.

Engineered Capabilities & Innovations

Automated PDF resume parsing with section-level entity extraction

Semantic matching score against 50+ standardized tech job archetypes

Personalized week-by-week learning roadmap targeting identified technical gaps

Exportable ATS-friendly resume rewrite suggestions

Empirical Results & Benchmarks

Analyzed over 400 student resumes, achieving 89% user satisfaction on the clarity and relevance of generated study roadmaps.

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Have Questions About This System?

I am always glad to discuss technical architecture, benchmarks, or potential collaboration.

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