LinkedIn Jobs Scraper

Scrape public LinkedIn job listings without requiring a LinkedIn account or login. Extract job titles, companies, locations, salaries, descriptions, applicant counts, and application links.

Features

• No Login Required -- scrapes LinkedIn's public job search pages
• Rich Data Extraction -- titles, companies, locations, salaries, full descriptions, criteria, apply links
• Flexible Filters -- keyword, location, time posted, job type, experience level, remote/on-site/hybrid
• Multiple Parsing Strategies -- handles LinkedIn's frequent HTML changes with 3 fallback strategies
• User-Agent Rotation -- 8 rotating browser User-Agents to reduce detection
• Respectful Crawling -- built-in rate limiting and random delays
• Pagination -- automatically pages through results (up to 1000 per search)
• PPE Billing -- pay-per-event pricing (charges per job scraped)
• Proxy Support -- works with Apify residential proxies for reliable results

Input Parameters

Parameter	Type	Default	Description
keyword	string	"software engineer"	Job title, skill, or company to search for
location	string	"United States"	City, state, country, or "Remote"
timePosted	enum	"any"	any, past24h, pastWeek, pastMonth
jobType	enum	"any"	any, fulltime, parttime, contract, internship, temporary, volunteer
experienceLevel	enum	"any"	any, internship, entry, associate, mid-senior, director, executive
remoteFilter	enum	"any"	any, remote, onsite, hybrid
maxResults	integer	25	Max jobs to scrape (0 = unlimited)
scrapeJobDetails	boolean	true	Visit each job's detail page for full description
maxConcurrency	integer	2	Concurrent requests (keep low for LinkedIn)
proxyConfiguration	object	-	Apify proxy config (recommended: residential)

Example Input

{
    "keyword": "data scientist",
    "location": "San Francisco, CA",
    "timePosted": "pastWeek",
    "jobType": "fulltime",
    "experienceLevel": "mid-senior",
    "remoteFilter": "remote",
    "maxResults": 50,
    "scrapeJobDetails": true,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Output

Each scraped job listing contains the following fields:

Field	Type	Description
title	string	Job title
company	string	Company name
location	string	Job location
salary	string	Salary range (if displayed)
jobId	string	LinkedIn job posting ID
jobUrl	string	Direct link to job posting
postedDate	string	Approximate posting date (ISO 8601)
postedDateRaw	string	Raw date text from LinkedIn
employmentType	string	Full-time, Part-time, Contract, etc.
experienceLevel	string	Entry, Mid-Senior, Director, etc.
industry	string	Industry classification
jobFunction	string	Job function/department
description	string	Full job description (plain text)
descriptionHtml	string	Full description (HTML)
criteria	object	All job criteria from the detail page
applicantCount	string	Number of applicants text
companyUrl	string	Company LinkedIn page URL
companyDetails	array	Company size, industry, etc.
applyUrl	string	External application URL (if available)
benefits	array	Listed benefits/perks
searchKeyword	string	The keyword used in the search
searchLocation	string	The location used in the search
scrapedAt	string	Timestamp when this job was scraped

Example Output

{
    "title": "Senior Data Scientist",
    "company": "Stripe",
    "location": "San Francisco, CA (Remote)",
    "salary": "$180,000 - $250,000/yr",
    "jobId": "3847291056",
    "jobUrl": "https://www.linkedin.com/jobs/view/3847291056/",
    "postedDate": "2026-02-25T00:00:00.000Z",
    "postedDateRaw": "4 days ago",
    "employmentType": "Full-time",
    "experienceLevel": "Mid-Senior level",
    "industry": "Technology, Information and Internet",
    "jobFunction": "Engineering and Information Technology",
    "description": "We're looking for a Senior Data Scientist to join our Risk team...",
    "descriptionHtml": "<p>We're looking for a Senior Data Scientist...</p>",
    "criteria": {
        "seniority_level": "Mid-Senior level",
        "employment_type": "Full-time",
        "job_function": "Engineering and Information Technology",
        "industries": "Technology, Information and Internet"
    },
    "applicantCount": "127 applicants",
    "companyUrl": "https://www.linkedin.com/company/stripe",
    "companyDetails": ["5,001-10,000 employees", "Financial Services"],
    "applyUrl": "https://stripe.com/jobs/listing/senior-data-scientist/...",
    "benefits": ["Health insurance", "401(k)"],
    "searchKeyword": "data scientist",
    "searchLocation": "San Francisco, CA",
    "scrapedAt": "2026-03-01T12:00:00.000Z"
}

Use Cases

• Job Market Research -- analyze hiring trends by role, location, and industry
• Salary Benchmarking -- collect salary data across companies and regions
• Competitive Hiring Analysis -- track which companies are hiring for specific roles
• Lead Generation -- identify companies with open positions for B2B outreach
• HR & Recruiting -- monitor competitor job postings and compensation
• Career Planning -- track demand for specific skills and technologies
• Talent Market Intelligence -- understand which markets have the most openings
• Academic Research -- study labor market dynamics and trends

Tips for Best Results

1. Use Proxies -- LinkedIn actively blocks datacenter IPs. Use Apify residential proxies for reliable scraping.
2. Keep Concurrency Low -- set maxConcurrency to 1-2. LinkedIn is aggressive about rate limiting.
3. Start Small -- test with maxResults: 10 before scaling up.
4. Specific Keywords -- more specific keywords yield better results (e.g., "senior react developer" vs "developer").
5. Off-Peak Hours -- scraping during off-peak hours (weekends, nights) may reduce blocking.

Limitations

• LinkedIn may change their public page structure at any time. The scraper uses 3 fallback parsing strategies to handle this.
• Salary data is only available when the employer or LinkedIn chooses to display it (roughly 30-40% of listings).
• LinkedIn caps public search pagination at approximately 1,000 results.
• Some job details may require authentication to access -- the scraper extracts what is publicly available.
• Rate limiting is common. Using residential proxies significantly improves reliability.

Cost / Pricing

This actor uses Pay-Per-Event (PPE) pricing. You are charged for each job listing successfully scraped. There is no charge for failed requests or blocked pages.

Technical Details

• Built with CheerioCrawler from Crawlee (no browser overhead)
• ESM modules (Node.js 20+)
• Handles LinkedIn's auth walls, CAPTCHAs, and 999 error codes
• Automatic retry with exponential backoff on failures
• Deduplicates results by LinkedIn job ID

Integration — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("sovereigntaylor/linkedin-jobs-scraper").call(run_input={
    "keyword": "data scientist",
    "location": "San Francisco, CA",
    "timePosted": "pastWeek",
    "maxResults": 50,
    "scrapeJobDetails": True,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
})

for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    salary = job.get("salary", "Not listed")
    print(f"{job['title']} at {job['company']} — {salary}")

Integration — JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('sovereigntaylor/linkedin-jobs-scraper').call({
    keyword: 'data scientist',
    location: 'San Francisco, CA',
    timePosted: 'pastWeek',
    maxResults: 50,
    scrapeJobDetails: true,
    proxyConfiguration: {
        useApifyProxy: true,
        apifyProxyGroups: ['RESIDENTIAL']
    }
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(job => {
    console.log(`${job.title} at ${job.company} — ${job.salary || 'Not listed'}`);
});

Related Actors

• LinkedIn Company Scraper — Scrape LinkedIn company profiles
• LinkedIn Profile Scraper — Extract LinkedIn profile data
• Indeed Scraper — Compare with Indeed job listings
• Indeed Salary Scraper — Salary data and compensation benchmarks
• Glassdoor Scraper — Company reviews and salary data