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LinkedIn Jobs Scraper — No Login, No Account Risk

Scrape LinkedIn job listings at scale from the public jobs index. No login, no cookies, no account to get banned. Filter by keywords, location, date, job type, experience level, and workplace type. Optionally pull each job's full description, seniority, employment type, function, industries, and applicant count.

What does LinkedIn Jobs Scraper do?

This actor extracts job listings from LinkedIn's public jobs search — the same logged-out index you see in an incognito window. Because it never logs in, there is no account at risk and nothing for LinkedIn to ban. It runs as pure HTTP with a real browser TLS fingerprint, so it is fast and reliable.

Give it search filters or paste a LinkedIn jobs search URL, and it returns clean, structured job data ready for your dataset, CRM, or analytics pipeline. On the Apify platform you get scheduling, API access, exports (JSON/CSV/Excel), and residential proxy support out of the box.

Why use this scraper?

• No account risk — public data only, no cookies, no login, no bans.
• Structured filters — keywords, location, date posted, job type, experience, workplace type. No need to hand-craft URLs (but you can).
• Full job details — optional one-extra-request enrichment per job for description and criteria.
• Cheap — public job data is the lowest-cost LinkedIn target. Built for high volume.
• Clean output — deduplicated by job ID, structured fields, ready to use.

Perfect for: job-market research, recruiting and sourcing, competitive hiring analysis, salary benchmarking, building job boards, and lead generation for recruiting agencies.

How to use it

1. Enter Keywords (e.g., python developer) and a Location (e.g., London).
2. Optionally narrow with Date Posted, Job Types, Experience Levels, Workplace Type.
3. Set Maximum Results (LinkedIn caps each search at ~1000).
4. Leave Scrape Full Job Details on for descriptions and criteria, or turn it off for a faster, lighter run.
5. Click Save & Start. Results stream into the dataset.

Advanced: paste full LinkedIn jobs search URLs into Search URLs (build them in an incognito window, logged out) to override the structured filters.

Input

Output

{
"jobId":"4425526234",
"title":"Python Developer",
"company":"hackajob",
"companyUrl":"https://uk.linkedin.com/company/hackajob",
"location":"London, England, United Kingdom",
"postedDate":"2026-06-08",
"postedText":"2 weeks ago",
"jobUrl":"https://www.linkedin.com/jobs/view/4425526234",
"description":"We are looking for a Python Developer...",
"seniority":"Mid-Senior level",
"employmentType":"Full-time",
"jobFunction":"Engineering and Information Technology",
"industries":"Software Development",
"applicants":"Over 200 applicants"
}

You can download the dataset as JSON, CSV, Excel, or XML from the Storage tab.

Data fields

How much does it cost to scrape LinkedIn jobs?

Job listings are the cheapest LinkedIn data to scrape because they are fully public. Turn off Scrape Full Job Details for the lightest, fastest runs; turn it on when you need descriptions and criteria (one extra request per job).

Tips

• Use residential proxies for large runs — LinkedIn rate-limits datacenter IPs.
• LinkedIn caps each search at ~1000 results. To pull more, split into narrower searches (by city, by date window, by job type) and run them as multiple searchUrls.
• Details off = faster + cheaper. Leave it off if you only need title, company, location, and link.

FAQ

Do I need a LinkedIn account? No. This scrapes the public, logged-out jobs index. No login, no cookies.

Is this legal? It scrapes publicly available data. Courts have upheld scraping public LinkedIn data, but you are responsible for complying with applicable laws and LinkedIn's terms for your use case.

Why am I getting fewer than 1000 results? LinkedIn's public index caps each individual search. Split into narrower searches to get more coverage.

For bugs or feature requests, open an issue on the actor's Issues tab.