RemoteOK Jobs Scraper - Remote Hiring Data

Scrape remote job listings from RemoteOK and export clean hiring data in JSON, CSV, Excel or through the Apify API. The actor returns job title, company, location, remote tags, salary range when available, posted date, company logo, short description and the direct RemoteOK job URL.

RemoteOK is one of the best-known job boards for remote-first hiring. Recruiters, job aggregators, compensation analysts and recruiting agencies use it to monitor new remote roles, benchmark hiring demand, source companies that are actively expanding and build fresh remote-work datasets.

What does this actor do?

The actor reads RemoteOK's public job feed directly and normalizes the jobs into a flat dataset that is easy to use in spreadsheets, automations and databases. You can run it with a broad keyword such as python, sales or marketing, filter by a RemoteOK tag, filter by location text, or leave the filters broad and collect the newest remote jobs.

Because the source is a public JSON feed, the actor is fast and reliable. It does not need a browser, a proxy, login cookies or a paid API key. That makes it suitable for scheduled monitoring and daily Apify Store auto-tests.

Input

The input is intentionally simple:

{
  "keyword": "python",
  "tag": "",
  "location": "",
  "maxResults": 25
}

Use keyword for broad matching across job title, company, location, tags and description. Use tag when you want a narrower RemoteOK-style skill/category match. Use location only when you need location text from the posting; most jobs are remote and may use broad location labels.

Output

Each dataset item contains:

{
  "job_id": "123456",
  "title": "Senior Python Engineer",
  "company": "Example Inc",
  "location": "Worldwide",
  "remote": true,
  "tags": ["python", "backend", "api"],
  "salary_min": 120000,
  "salary_max": 180000,
  "currency": "USD",
  "posted_at": "2026-07-03",
  "description": "Short normalized job description...",
  "url": "https://remoteok.com/remote-jobs/...",
  "company_logo": "https://...",
  "source": "RemoteOK",
  "search": {
    "keyword": "python",
    "tag": "",
    "location": ""
  }
}

Use cases

Recruiting teams can track which remote-first companies are actively hiring in specific roles or technologies. Job boards can enrich their own listings with RemoteOK roles. Market researchers can measure demand for skills such as Python, React, AI, DevOps, design, sales or customer support. Lead-generation teams can identify companies that have current hiring budgets and outreach to them with staffing, software, training or recruiting services.

The actor is also useful for salary and compensation research. RemoteOK jobs often include salary ranges, so you can monitor remote compensation trends by keyword and tag over time.

Scheduling

For monitoring, create a saved task with your keyword and run it daily or weekly. Apify can send the output to a webhook, Make, Zapier, n8n, Google Sheets, Airtable or your own API endpoint.

Reliability

The actor uses a direct HTTP request to RemoteOK's JSON feed. It is intentionally lightweight: no browser launch, no residential proxy and no login session. It retries transient request failures and deduplicates jobs by job ID before pushing data.

Pricing

This actor uses pay-per-result pricing. You only pay for jobs pushed to the dataset, plus a small actor start event.

FAQ

Does this scrape private data?

No. It collects publicly available job listings from RemoteOK's public job feed.

Can I filter by skill?

Yes. Use the keyword field for broad matching and the tag field for skill/category matching.

Does it support salary data?

Yes, when RemoteOK includes salary minimum, salary maximum and currency in the source feed.

Does it require proxies?

No. The actor is designed to run directly from Apify without a proxy.

Can I run it on a schedule?

Yes. It is well suited for daily or weekly scheduled monitoring.

You might also like

• StepStone Scraper
• HiringCafe Scraper
• BuiltIn Jobs Scraper
• YC Jobs Scraper

Keywords

RemoteOK scraper, RemoteOK jobs API, remote jobs scraper, remote hiring data, remote work dataset, tech jobs scraper, Python jobs, React jobs, remote salary data, recruiting leads, job board data, Apify jobs scraper.

Data quality notes

The actor keeps the output intentionally flat so it can be joined with CRM records, enrichment tools, spreadsheets and BI systems without additional parsing. Identifiers are stable where the source registry provides them, and source-specific fields are preserved instead of being hidden behind a generic schema. This makes the dataset useful for both quick exports and repeatable monitoring workflows.

For lead-generation use, combine the package name and repository/homepage fields with a contact enrichment actor such as Website Contact Extractor. For market research, schedule the same query over time and compare downloads, version counts, favorites or timestamps. For developer-relations work, use keyword searches around frameworks, cloud providers, databases, AI tooling, testing libraries or migration targets to find projects that match your product category.

Tips for better searches

Use broad ecosystem terms when you want market maps, for example api, database, testing, ai, payments, kubernetes or analytics. Use exact package or framework terms when you want competitor monitoring. Run several narrow queries instead of one huge query when you need better coverage across a category.

Automation ideas

You can run this actor from Apify schedules, the API, a saved task, or an integration. Common workflows include weekly package tracking, dependency research, open-source lead discovery, security watchlists, trend dashboards and technology adoption reports. The actor is small enough to run frequently and cheap enough to include in larger enrichment pipelines.

Why this dataset has commercial value

Package metadata is a buying-intent signal for developer products. A project that depends on a framework, database, cloud service, testing tool or API category often has an active engineering team and an immediate technical context. That makes registry data useful beyond simple package lookup: it can feed sales research, partner discovery, ecosystem mapping, migration planning, content targeting and competitive analysis.

For best results, combine registry rows with repository metadata, website contact extraction and company enrichment. The package registry tells you what technology is being used; enrichment tells you who owns the project and how to reach them. That combined workflow is where these lightweight package actors become useful business tools instead of one-off lookup scripts.