LinkedIn Job Scraper - No API, 1000+ Listings avatar

LinkedIn Job Scraper - No API, 1000+ Listings

Pricing

from $1.50 / 1,000 results

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LinkedIn Job Scraper - No API, 1000+ Listings

LinkedIn Job Scraper - No API, 1000+ Listings

Extract LinkedIn job posts using Google Search to bypass limits. Get job titles, companies, salaries, and descriptions. Perfect for recruitment and lead research.

Pricing

from $1.50 / 1,000 results

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0.0

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Developer

Vhub Systems

Vhub Systems

Maintained by Community

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0

Bookmarked

4

Total users

2

Monthly active users

3 days ago

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LinkedIn Job Scraper 💼

Scrape public job listings from LinkedIn — titles, companies, locations, salary ranges, and job descriptions. No LinkedIn account required.

What you get

  • 💼 Job title, company name, location (remote/hybrid/onsite)
  • 💰 Salary range (when listed)
  • 📋 Full job description
  • 🏢 Company size, industry
  • 📅 Posted date, number of applicants
  • 🔗 Direct application URL

Quick Start

  1. Enter keywords and/or location
  2. Optionally filter by job type, experience level, or date posted
  3. Click Start

❓ Frequently Asked Questions

Do I need a LinkedIn account or cookies? No — this scraper accesses publicly listed jobs without authentication.

How many jobs can I scrape per search? LinkedIn shows up to 1,000 results per query. Use multiple queries to expand coverage.

Why are some job descriptions truncated? LinkedIn sometimes requires a click to expand descriptions. The scraper attempts to capture full text but some listings may be partial.

Can I filter by remote/hybrid/on-site? Yes — use the workplaceType input parameter.

How do I get jobs from a specific company? Set companyName in the input, or use a LinkedIn company jobs URL directly.

Input parameters

FieldTypeDefaultDescription
keywordsstringrequiredJob search keywords, e.g. "python developer"
locationstringCity or region, e.g. "New York", "Remote"
maxResultsnumber50Max job listings to return
datePostedstringanyFilter: past-24h, past-week, past-month
jobTypestringanyFilter: full-time, part-time, contract, internship
experienceLevelstringanyFilter: entry, mid, senior, director

Output example

{
"title": "Senior Python Developer",
"company": "Stripe",
"location": "Remote",
"salary": "$150,000 – $200,000/yr",
"description": "We are looking for...",
"postedAt": "2024-11-18",
"applicants": "200+ applicants",
"url": "https://linkedin.com/jobs/view/..."
}

Pricing

Pay per result — you only pay for job listings actually scraped.

Why Scrape LinkedIn Jobs?

LinkedIn is the world's largest professional network with 1 billion+ members and millions of active job postings. Use cases:

  • Job market research — track which roles are in demand by location, industry, or seniority
  • Salary intelligence — collect salary ranges listed in job descriptions
  • Skills gap analysis — identify the most requested skills in your field
  • Recruiting pipeline — build lists of open positions at target companies
  • Competitive intel — monitor when competitors are hiring (signals growth or new product areas)
  • Academic research — study labor market trends, remote work patterns, or skill demand
  • HR analytics — benchmark your job descriptions against industry standards

What Data Is Extracted?

FieldDescription
titleJob title
companyCompany name
locationCity / Remote / Hybrid
salarySalary range (if listed)
jobTypeFull-time / Part-time / Contract
experienceLevelEntry / Mid / Senior / Director
postedAtDate posted
descriptionFull job description text
applyUrlDirect application link
companyUrlLinkedIn company page
industryTagsIndustry categories

How Many Jobs Can I Scrape?

LinkedIn shows up to 1,000 results per search query. To get more coverage:

  • Use multiple location-based queries (e.g., "Berlin", "Munich", "Hamburg")
  • Filter by datePosted to stay within rate limits
  • Use experienceLevel to split large searches into smaller batches

LinkedIn's public job listings are publicly accessible. The hiQ v. LinkedIn ruling (2022) confirmed that scraping publicly available data does not violate the Computer Fraud and Abuse Act (CFAA) in the US. Always use data responsibly and in compliance with local laws.