elliottdehn/open-jobs: ~3M live jobs from 36 ATS, enriched with LLM-extracted fields + embeddings, released CC0. Includes agent tooling to search them (hull -> learn -> rank).

3.1 million current job postings, crawled every day from 65,000 company career sites,
every one graded fresh, stale, re-stamped, or ghost.
Free. No account. No business model.

Try it in your browser  ·  Use it with your agent  ·  Take the data

_{Building something on this? Say what. If you need it there every morning, say so, and I'll tell you honestly what I can commit to.}

Every listing wears its verdict

Job boards know which listings are dead and will not tell you, because their revenue depends on a shelf that looks full. Open Jobs crawls the career sites themselves and records the day it first sees every posting. That clock cannot be re-stamped. A model learns how long each kind of posting typically lives, and every job is graded against par:

| | verdict | what it means | |---|---|---| | 🌱 | Fresh | younger than postings like it. The market moves fast here. Apply now. | | 🥀 | Stale | an outlier survivor. Hard to fill, which can mean thin competition. | | 🔁 | Re-stamped | claims to be newer than when the crawler first saw it. Caught. | | 👻 | Ghost | open for over a year. The dataset holds 40,000 postings over five years old. |

Fresh is what you see by default. The rest is one click away, labelled.

Try it in your browser

backend.dehnbostele.workers.dev

Type a job title, where you want to work, and a few sentences about the job you want. The page writes the posting, finds its neighborhood among 3.1 million openings, and shows you the fresh ones first. Say yes or no; a yes pulls in more jobs like it, and Rerank re-sorts the list when you ask, never underneath you. No account. Nothing except what you type is sent to the server.

Use it with your agent

Paste this into Claude Code, Codex, Cursor, or whatever you use:

Clone https://github.com/elliottdehn/open-jobs to help me find a job.

Or install it as a Claude Code plugin:

/plugin marketplace add elliottdehn/open-jobs
/plugin install job-search@open-jobs

Your agent interviews you, writes the description of the job you want, pulls the nearest openings onto your disk, and hands you a shortlist of fresh, eligible matches ranked by how well they fit. On a laptop it also builds a local search page that learns from your yes and no. Five minutes, start to shortlist. Your labels, notes, and resume never leave your machine. You need uv; everything is uv run tools/jobs.py .

Agents: you MUST read AGENTS.md in full before doing anything else in this repo.

How it works

1. Crawl. One Cloudflare Durable Object per career site, 65,000 of them, each wakes at its own

1. Grade. A nightly batch folds the fleet into one dataset, trains the estimators (posting age,

1. Search, locally. Your description of the job you want is embedded once, its nearest groups

Around 11,000 lines of code. Roughly a dollar a day to run. Design and the daily workflow: backend/DOCS.md. Enrichment fields: backend/FIELDS.md.

Take the data

One link: open-jobs-latest.tar, about 13 GB, every open posting with its full description, a 1536-dim embedding, and company fields, as one parquet file per applicant tracking system, rebuilt nightly. Resumes if interrupted.

Or three commands, which also give you a query shell over it:

git clone https://github.com/elliottdehn/open-jobs
cd open-jobs
uv run tools/jobs.py export

Needs uv, one line to install: curl -LsSf https://astral.sh/uv/install.sh | sh (or brew install uv; on Windows winget install astral-sh.uv).

Three commands and the whole dataset is on your disk: every open posting with its full description, a 1536-dim embedding, and company fields, as one parquet file per applicant tracking system (~13 GB, resumable). Then uv run tools/jobs.py sql "SELECT title, company, location FROM jobs LIMIT 20" queries it with DuckDB. /data/ lists every published file with sizes, build dates, and how to read each in place.

The corpus is published as static files: a manifest (a tree of a few thousand groups of similar jobs, with labels and exemplars), centroids, and one JSON per group with titles, companies, locations, URLs, full description text, and float32 vectors. tools/jobs.py fetch pulls any set of groups into a local parquet you can query with DuckDB. The API also answers per-posting questions: POST /status with a list of ats/slug#id keys returns open or removed with timestamps, straight from the crawler's records.

Mirror the search index

Several people already take the whole tree every night, so here is the contract. The index is static files: manifest.json, centroids.bin, and one JSON per group.

1. GET /data/manifest.json. Read groups (this build's prefix, e.g. groups/2026-09-09/), built_at

1. Fetch /data/centroids.bin and /data/.json for every leaf id. One publish is one

1. Repeat when built_at changes. Publishes land once a day, in the morning UTC.

History is published too. Every day's diff against the day before, one row per event with the full job record (added, removed, changed, and the previous version of changed), sits under /data/diffs/, each with a lite/ twin that drops the vectors and keeps the text only where a mirror needs it, and a daily ledger of every job the crawler has ever recorded, open or removed, with its first-seen and removed dates, under /data/ledger/. /data/diffs/index.json and /data/ledger/index.json list what is there. Layout, schema, and endpoints: backend/DOCS.md.

The ideas channel

⏰ The repo ships a permission (.claude/settings.json) that lets an agent post short improvement notes (file:line, idea) to a shared Slack channel. That permission is a technical default, not consent: the agent gets to work without asking, and the first time it has an idea worth sharing it asks whether it may post it. On a yes it posts; on a no it immediately opts the person out with uv run tools/optin-ideas.py --out. Nothing about the person, their JD, labels, or data is ever posted. The wording and rules are in AGENTS.md under "#multipenny-ideas"; an agent that posts without asking is misbehaving.

License

See LICENSE.