AI / ML · 2026
Lincoln
Tinder for jobs. Swipe through scraped postings and a recommender learns your taste from every swipe — no forms, no filters, just implicit feedback. Swipe right, and it drafts you a tailored resume.
Watch the Demo
▶ Sound on. Swipe right on the good ones — it retrains on your taste every 20 swipes, then drafts the resume.
The Loop
Scrape postings → swipe left/right → after every 20 new swipes, a background task retrains a TF-IDF + Logistic Regression model on your swipe history → the feed re-ranks toward what you actually like. No preference forms, no keyword filters — the model reads your taste from behavior alone.
How It's Built
Swipe UI
Next.js + TypeScript front-end — postings as cards, one decision at a time.
Self-retraining recommender
TfidfVectorizer + LogisticRegression over your swipe history; trains once 20 labeled swipes exist, then retrains automatically every 20 more. Artifacts pickled and reloaded on boot.
Job-board scraper
FastAPI + SQLAlchemy backend keeps the deck stocked with fresh postings in Postgres.
Resume crafting
Right-swiped a job? Claude drafts a resume tailored to that exact posting via the Anthropic API.
Status
Dockerized and deployed on Railway — scraper, recommender, and resume crafting all running as one service.