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Jobs & recruitment

Sweep Every We Work Remotely Category in One Run

One run across all categories — the whole remote-job market surface as a single dataset.

Sep 16, 2026 · 2 min read · 483 words
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The whole remote job market, one input field wide. Thirdwatch's We Work Remotely Jobs Scraper pulls We Work Remotely's category feeds — the largest remote-job board — with full descriptions and apply links per row.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why sweep every category

For market-level analysis — which categories are hiring, how volumes shift week over week — you need the whole board, not one category at a time.

categories takes the full list; the run returns the combined dataset with category labelling each row.

The board's own feeds carry every posting with the full description, so the scrape is clean and complete.

How does this compare to the alternatives?

Approach Cost model Coverage Effort
Manual board browsing Free What you can read Doesn't scale
Job aggregator subscription Monthly fee Their coverage, their schema Vendor lock-in
Thirdwatch jobs scraper Pay per job row The whole board, structured One run

Why this Actor

  • All categories supported — programming through writing, QA, HR and more.
  • Full job descriptions on the row, not just titles.
  • region captures the posting's geographic restriction explicitly.
  • Keyword query filter runs across title, company and description.
  • Feed-based — fast, cheap, and stable.

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — categories takes the targets, category names map to the site's own feeds — programming, design, marketing, sales, product, qa, writing, hr, other.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per job.

Step 3: Use the output

Each row carries title, company, region restriction, full description, publish date, and the apply link.

{
  "categories": [
    "programming",
    "design",
    "marketing",
    "sales",
    "product",
    "qa",
    "writing",
    "hr",
    "other"
  ],
  "maxJobs": 100
}

Each dataset row looks like:

{
  "title": "Senior Backend Engineer",
  "company": "Acme Inc",
  "url": "https://weworkremotely.com/remote-jobs/acme-senior-backend-engineer",
  "guid": "wwr-12345",
  "category": "programming",
  "region": "Anywhere",
  "publishedAt": "2026-09-10T14:00:00Z",
  "description": "We're looking for a senior backend engineer ..."
}

What to watch for

The category feeds carry recent postings (~100 per category) — for a full historical corpus, run on a schedule and accumulate. Region parsing is best-effort where postings don't declare one.

Related use cases

Run the We Work Remotely Jobs Scraper on Apify Store — pay per result, free to try, no credit card to test.

Frequently asked questions

Which categories are supported?

All of them — `programming`, `design`, `marketing`, `sales`, `product`, `qa`, `writing`, `hr`, `other`. Pass several in `categories` for a combined pull.

Does it include the job description?

Yes — the full posting body comes back in `description`, not just the title.

How far back does coverage go?

The feeds carry each category's recent postings (~100); older ones age out of the feed — run on a schedule for continuous coverage.

What is the `region` field?

The posting's stated geographic restriction — 'US Only', 'Anywhere', etc. — parsed from the listing.

Can I filter by keyword?

Yes — `query` matches against title, company, and description text.

Is there an apply link per job?

Yes — `url` is the listing link and `guid` gives a stable ID for dedup.

Related

Try it yourself

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