Why it exists

Resume Matcher's site makes the problem painfully clear — three dead ends job seekers hit today:

1. Rewriting by hand — you reshuffle the same bullet points for every posting; by the time the resume fits, the role has closed.
2. Pasting into a chatbot — the chatbot invents metrics you can't defend in an interview, and your work history leaves your machine.
3. Sending the same resume everywhere — the job asks for Kubernetes and gRPC, your resume says "infrastructure". Recruiters search for exact words.

Resume Matcher was built to fix all three at once: a free, open-source tool (28k+ GitHub stars, 200,000+ users) that tailors your resume to a specific job description using an LLM you choose — including a fully local model via Ollama — while keeping every fact intact and everything stored on your machine.

How it works

1. Your master resume — everything you've done, written once. Import a PDF or DOCX, or edit in the builder.
2. The job description — paste the posting. The model extracts what it actually asks for.
3. The match — each keyword is checked against your resume with a score: go found, kubernetes found, terraform missing. Nothing is hidden from you.
4. The tailored resume — bullets are reworded to lead with what the job asks for, shown as before/after diffs. Nothing is saved until you confirm. Same facts, nothing invented.

Main features

• Review builder — edit every section next to a live, paginated preview; download the finished PDF.
• Keyword match rate — see which job-description keywords your resume already contains, highlighted.
• Application tracker — every confirmed resume becomes a card on a Kanban board, from Applied to offer or rejection.
• Cover letters & interview prep — generated from your resume and the posting, so they tell the same story.
• Enrichment — the tool asks about your real work and turns the answers into stronger bullets, so your master resume improves with every job.
• Seven templates — single and two column, modern, clean, vivid, and a LaTeX-style one.
• Any model you like — OpenAI, Anthropic, Gemini, DeepSeek, OpenRouter, Groq, Azure, or fully local with Ollama. API keys are stored encrypted.
• Private by default — resumes, jobs and the tracker live in a SQLite file on your machine.
• Seven languages — English, Spanish, Chinese, Japanese, Brazilian Portuguese, French, Korean.

Getting started

You need Docker (or Python 3.13 + Node 22 if you prefer no containers):

git clone https://github.com/srbhr/Resume-Matcher.git
cd Resume-Matcher
docker compose up -d
# then open http://localhost:3000

Add an API key in Settings (or point it at Ollama), upload your resume, paste a job — your first tailored resume takes about five minutes.

Who it's for

• Software engineers applying to many distinct roles (backend, SRE, ML platform, frontend) where each posting demands different keywords.
• Privacy-conscious job seekers who refuse to paste their work history into a cloud chatbot.
• Anyone who wants AI assistance with receipts — diffs and match scores instead of a black-box rewrite.

How it compares

Useful links

• Website: https://resumematcher.fyi/
• GitHub: https://github.com/srbhr/Resume-Matcher
• Docs: https://docs.resumematcher.fyi/
• Discord community
• Resume guides for engineers (software engineer, CS student, FAANG, LaTeX resumes) on the blog

Notes

• Part of the Vercel OSS program, Claude for Open Source and Codex for Open Source; backed by Anthropic, OpenAI, Vercel and others.
• Donation-supported — no ads, no paywall.
• The maintainer is explicit that the tool never invents facts: it rewords what's already there, and flags missing keywords honestly (sometimes the right answer is "learn Terraform", not "hide the gap").