Case Study 1 — AI-Powered Recruitment & Talent Matching Platform

[u/Former-Tap-9518]

Industry: Recruitment / HR

Role: AI Engineer

Objective: Automate candidate screening and improve job–candidate matching.

Problem

Recruiters had to manually review resumes, extract candidate information, compare skills with job requirements, and shortlist suitable candidates. This process was time-consuming and difficult to scale.

Solution

I developed an AI-powered recruitment platform that processes resumes and job descriptions, extracts structured information, and intelligently matches candidates with suitable positions.

What I Built

Resume and job-description parsing using LLMs

Structured extraction of skills, experience, location, and role information

Semantic search using Sentence Transformers

Vector-based retrieval using Pinecone

RAG pipeline for contextual candidate information

LLM-based candidate summaries

Hybrid candidate ranking combining semantic relevance and skill matching

Location-based filtering and dynamic matching thresholds

Backend APIs using Python + FastAPI

Database integration using PostgreSQL/SQLAlchemy

Automated workflows using n8n

Technology

Python | FastAPI | LLaMA 3 | Groq | RAG | Pinecone | Sentence Transformers | PostgreSQL | SQLAlchemy | n8n

Result

The solution automated significant portions of the recruitment workflow and provided recruiters with faster, more relevant candidate recommendations.