LinkedIn Jobs Scraper

Scrape public LinkedIn job search results and job detail pages — title, company, location, workplace type, employment type, seniority, description, apply URL, posted date, and applicants (when public). Built with TypeScript, Crawlee CheerioCrawler, and LinkedIn guest/public job endpoints (no login required for many public listings).

Run it on the Apify platform for scheduling, API access, proxy rotation, monitoring, and dataset exports (JSON, CSV, Excel).

What does LinkedIn Jobs Scraper do?

Given LinkedIn job search URLs and/or keywords + location, this Actor:

1. Converts public search URLs into LinkedIn guest seeMoreJobPostings API requests
2. Paginates search results until maxJobs is reached
3. Optionally opens each job’s guest detail page for full description and criteria
4. Deduplicates jobs by jobId
5. Pushes structured dataset items
6. Exports JOBS.csv and SUMMARY.md to the key-value store

Why use LinkedIn Jobs Scraper?

• Recruiting pipelines — build candidate-role inventories from public listings
• Sales / lead generation — find companies hiring for target roles
• Market research — track job titles, locations, and seniority mix over time
• Competitive intel — monitor which skills and roles competitors post

How to scrape LinkedIn jobs

1. Open the Actor in Apify Console
2. Paste a LinkedIn jobs search URL or set keywords + location
3. Set Max jobs and enable/disable full descriptions
4. Keep concurrency low and enable Apify Proxy (residential recommended)
5. Click Start
6. Download results from the Dataset tab or key-value store exports

Input

Field	Type	Default	Description
searchUrls	string[]	[]	Public LinkedIn job search URLs
keywords	string	""	Keywords used to build a search URL
location	string	""	Location paired with keywords
maxJobs	integer	50	Max unique jobs (by jobId)
maxConcurrency	integer	2	Concurrent HTTP requests
maxRequestRetries	integer	3	HTTP retry count
requestDelayMs	integer	1000	Delay used for rate limiting
proxyConfiguration	object	Apify Proxy on	Proxy settings
includeDescription	boolean	true	Fetch job detail pages for full description

Example (search URL):

{
    "searchUrls": [
        "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States"
    ],
    "maxJobs": 50,
    "maxConcurrency": 2,
    "maxRequestRetries": 3,
    "requestDelayMs": 1000,
    "proxyConfiguration": { "useApifyProxy": true },
    "includeDescription": true
}

Example (keywords + location):

{
    "keywords": "account executive",
    "location": "New York, United States",
    "maxJobs": 25,
    "includeDescription": true,
    "proxyConfiguration": { "useApifyProxy": true }
}

See examples/input.json.

Output

Each dataset item is one job:

{
    "jobId": "4123456789",
    "title": "Senior Software Engineer",
    "company": "Acme Corp",
    "companyUrl": "https://www.linkedin.com/company/acme-corp",
    "location": "San Francisco, CA",
    "workplaceType": "Remote",
    "employmentType": "Full-time",
    "seniority": "Mid-Senior level",
    "description": "Build scalable backend services in TypeScript and Node.js...",
    "postedAt": "2026-07-01",
    "applicants": "Over 200 applicants",
    "applyUrl": "https://www.linkedin.com/jobs/view/4123456789/?isApplication=true",
    "jobUrl": "https://www.linkedin.com/jobs/view/4123456789",
    "scrapedAt": "2026-07-13T12:00:00.000Z",
    "error": null
}

You can download the dataset as JSON, HTML, CSV, or Excel. The Actor also writes:

Key-value record	Description
JOBS.csv	All job rows as CSV
SUMMARY.md	Markdown summary table of results

Data fields

Field	Description
jobId	LinkedIn job posting ID
title	Job title
company	Hiring company name
companyUrl	LinkedIn company URL when available
location	Location string from the listing
workplaceType	Remote / Hybrid / On-site (inferred when possible)
employmentType	Full-time, Part-time, Contract, etc.
seniority	Seniority level when public
description	Full text when includeDescription is true
postedAt	Posted date or relative time
applicants	Public applicants caption
applyUrl	Application link when available
jobUrl	Canonical public job URL
scrapedAt	ISO scrape timestamp
error	Soft error for blocked/partial records

Pricing

Pay-per-event (PPE): $0.003 per job (dataset item), plus a small Actor-start fee.

Estimate: 50 jobs ≈ $0.15.

Tips

• Prefer Apify Proxy residential if you hit auth walls, captchas, or empty results
• Keep maxConcurrency at 1–3 and requestDelayMs around 1000–2000 ms
• Set includeDescription: false for faster/cheaper runs when you only need titles and companies
• Use stable public search URLs from an incognito browser session
• Unit tests use HTML fixtures so CI does not depend on live LinkedIn access

Limitations

• Scrapes public/guest LinkedIn job pages only — not authenticated feed data
• LinkedIn frequently shows auth walls or rate limits; proxy + low concurrency help but do not guarantee 100% coverage
• Cheerio parses static HTML. Heavily client-rendered views may return fewer fields
• Some fields (applicants, apply URL, full description) are only present on detail pages
• Respect LinkedIn Terms of Service and applicable laws; use data responsibly

Technical notes

• Search pagination uses
  https://www.linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search?...&start=N
• Job details use
  https://www.linkedin.com/jobs-guest/jobs/api/jobPosting/{jobId}
• Extraction strategies: DOM job cards, JSON-LD JobPosting, job criteria lists
• Graceful handling of auth walls / blocks: logs a warning and falls back to search-card data when detail is blocked

Development

cd factory/linkedin-jobs-scraper
npm install
npm test
npm run build
apify run

License

Apache-2.0