LinkedIn Jobs Scraper - $1/1k, Salaries & Skills

Unofficial Actor. This tool is independent and is not affiliated with, endorsed by, or sponsored by LinkedIn. It collects only publicly available job listings and never uses LinkedIn credentials, cookies, or private APIs.

Description

Scrape LinkedIn job listings at scale and turn them into a clean, deduplicated dataset — job titles, companies, salaries, required skills, workplace type, experience level, applicant counts, and more. This LinkedIn Jobs scraper runs from simple keywords and locations with no login and no API key. Export to JSON, CSV, Excel, or HTML, or pull via the Apify API.

Scrape LinkedIn Jobs at scale with this production-ready Apify Actor. Supply job keywords and locations, and the Actor extracts comprehensive job listing data including titles, companies, descriptions, salaries, required skills, workplace type, job type, experience level, applicant counts, and more.

Built on Crawlee's PlaywrightCrawler with residential proxy rotation, session pool management, and intelligent anti-bot countermeasures, this Actor reliably scrapes LinkedIn without getting blocked. Each search supports pagination up to 500 job listings, and multiple keyword + location combinations can be run in a single execution.

Deduplication by LinkedIn job ID ensures clean, unique results. A pay-per-event model charges $1.00 per 1,000 successfully scraped jobs, making it affordable at any scale.

Use Cases

1. HR & Recruitment Research — Benchmark job titles, salaries, required skills, and workplace trends across markets and industries to inform hiring strategy.
2. Job Aggregators — Feed LinkedIn job data into your own job board, comparison site, or analytics dashboard with structured, deduplicated records.
3. Salary Benchmarking — Collect salary ranges from job listings to analyse compensation trends by role, location, experience level, and company size.
4. Talent Mapping — Identify which companies are hiring for specific roles in specific regions, and map competitor hiring activity over time.
5. Competitor Hiring Analysis — Monitor what skills, seniority levels, and locations your competitors are hiring for, and detect strategic shifts.

Sample Output

{
  "jobTitle": "Software Engineer",
  "companyName": "Google",
  "companyLinkedInUrl": "https://www.linkedin.com/company/google/",
  "jobLocation": "London, England",
  "workplaceType": "Hybrid",
  "jobType": "Full-time",
  "experienceLevel": "Mid-Senior level",
  "postedDate": "Posted 2 weeks ago",
  "numberOfApplicants": 47,
  "jobDescription": "Google's software engineers develop the next-generation technologies...",
  "requiredSkills": ["JavaScript", "Python", "Kubernetes"],
  "salaryRange": "$120,000 - $180,000",
  "applyUrl": "https://www.linkedin.com/jobs/view/123456789/",
  "jobId": "123456789",
  "companySize": null,
  "companyIndustry": null,
  "easyApply": true,
  "keywordUsed": "software engineer",
  "locationUsed": "London, UK",
  "scrapedAt": "2026-06-08T13:30:00.000Z"
}

Pricing

Unit	Price
Per 1,000 jobs	$1.00
Actor start	$0.00005 per GB of memory

Charges are incurred only when a job record is successfully scraped and pushed to the dataset. There are no upfront fees, no monthly minimums, and no hidden costs.

A job is saved and charged only when it carries a real job title plus a company or a description. Blocked pages and empty results are never saved and never charged, and the run stops as soon as your maxResults or your spending limit is reached.

Field Availability

LinkedIn does not publish every field on every listing. Fields that a listing does not expose are returned as null rather than guessed, so salaryRange, numberOfApplicants, companySize, and companyIndustry are frequently null. When LinkedIn shows no explicit skills list, requiredSkills is inferred from the job description using whole-word matching.

Input Parameters

Parameter	Type	Required	Default	Description
keywords	string[]	Yes	—	Job titles, skills, or search terms
locations	string[]	Yes	—	City, region, or country
workplaceType	string[]	No	[]	Filter: remote, hybrid, onsite
jobType	string[]	No	[]	Filter: full-time, part-time, contract, etc.
experienceLevel	string[]	No	[]	Filter: entry, mid-senior, director, etc.
maxResults	number	No	50	Maximum total jobs across all searches
maxJobsPerSearch	number	No	25	Max jobs per keyword + location combination
proxyConfiguration	object	No	RESIDENTIAL	Apify proxy settings

How to Scrape LinkedIn Jobs (Step by Step)

1. Click Try for free / Run.
2. Enter your job keywords (titles or skills) and locations (city, region, or country).
3. Optionally filter by workplace type, job type, and experience level.
4. Set Max Results and Max Jobs Per Search — start small to test.
5. Run, then export results as JSON, CSV, Excel, or HTML, or pull them via the Apify API.

Technical Details

• Runtime: Node.js 20 + Playwright (Chrome)
• SDK: Apify SDK v3 + Crawlee v3
• Proxy: Residential proxy rotation (required for LinkedIn)
• Anti-bot: Session pool (max 20 uses), randomised delays, 3 retries with retryOnBlocked, authwall detection with session rotation
• Pagination: Offset paging over LinkedIn's public guest job endpoints, bounded by your limits
• Deduplication: By LinkedIn job ID across all searches
• Efficiency: Only the HTML document is fetched. Scripts, stylesheets, images, media, and fonts are all blocked, because every field comes from server-rendered markup

Responsible Use

This Actor is intended for lawful collection of publicly available information only. Users are responsible for ensuring their use complies with the source website's terms, robots.txt, applicable privacy laws, including India's DPDP Act, and all local regulations.

Do not use this Actor to collect, store, sell, or misuse personal data without a lawful basis. The Actor author is not responsible for misuse by end users.