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HackerRank Hiring Agent
HackerRank Hiring Agent is an AI resume-to-score pipeline that extracts structured PDF data, enriches it with GitHub signals, and outputs fair evaluations.
HackerRank Hiring Agent parses a resume PDF to Markdown, extracts sectioned JSON using a local or hosted LLM, augments the data with GitHub profile and repository signals, and produces an objective evaluation. The system uses pymupdfrag to convert PDF pages to text, calls the LLM per section using Jinja templates, fetches GitHub profile and repositories, and runs a strict-scored evaluation with fairness constraints. It is built for organizations or developers handling high volumes of intern applications who need to rank candidates before human review. It supports Ollama for local models like gemma4 and Google Gemini. Users configure the tool via environment variables and run it through a command-line interface to produce readable summaries, cached JSON, and CSV exports.
HackerRank Hiring Agent at a glance
Key features
- Extracts structured data from PDF resumes
- Enriches applicant data with GitHub signals
- Parses sections using Jinja templates
- Runs evaluations with fairness constraints
- Supports local models via Ollama
- Supports Google Gemini API
- Exports evaluation summaries to CSV
Use it for
- Ranking large volumes of intern applications
- Scoring resumes against role-specific rubrics
- Extracting JSON data from PDF resumes
- Analyzing candidate GitHub profiles and repositories
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