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LinkedIn Jobs Scraper — Salary, Description, Filters

Scrape LinkedIn job listings at scale without login or cookies. Fast HTTP-only scraper — no browser needed, no headless Chrome overhead. 2 modes: search by keywords/location with filters, or get full details for specific job URLs.

$2 per 1,000 results — extracts salary, description, seniority level, and applicant count that most competitors miss.

:mag: What Does It Do?

This actor scrapes LinkedIn job data using two modes plus an enrichment option:

1. Search — Find jobs by keywords and location with filters (date posted, job type, experience level, workplace type, company, sort order)
2. Detail — Get full details for specific job URLs or IDs (description, salary, seniority, employment type, industries, apply link)
3. Search + Enrich — Search for jobs, then automatically fetch full details for each result (combines both modes)

HTTP-only architecture means it runs 5-10x faster and costs 90% less than browser-based scrapers. No Playwright, no Puppeteer, no login required. Uses LinkedIn's public guest API endpoints.

:bar_chart: What Data Can You Extract?

Search Results

Detail Results (enrichDetails or detail mode)

All search result fields plus:

:bulb: Use Cases

• Job market research — analyze hiring trends by role, location, and industry at scale
• Salary benchmarking — collect salary data across companies and regions to benchmark compensation
• Competitor hiring analysis — track what roles competitors are hiring for and how aggressively
• Recruitment pipeline — build candidate sourcing lists from job postings and company data
• Lead generation from job postings — identify companies actively hiring as potential sales leads
• HR analytics — aggregate job data to understand workforce demand, skill requirements, and market gaps

:moneybag: How Much Does It Cost?

• $2 per 1,000 results ($0.002 each)

Competitors charge $5-8 per 1,000 results. This actor is 3-4x cheaper with salary and description data included.

:inbox_tray: Input

Search by Keywords

{
"mode":"search",
"keywords":"data engineer",
"location":"San Francisco, CA",
"maxResults":100,
"datePosted":"pastWeek",
"jobType":"full-time",
"workplaceType":"remote"
}

Get Job Details

{
"mode":"detail",
"urls":[
"https://www.linkedin.com/jobs/view/4370317193",
"https://www.linkedin.com/jobs/view/software-engineer-at-google-4370317193",
"4370317193"
]
}

Search + Enrich with Full Details

{
"mode":"search",
"keywords":"product manager",
"location":"New York",
"maxResults":50,
"enrichDetails":true,
"experienceLevel":"mid-senior",
"sortBy":"recent"
}

:outbox_tray: Output Example

Detail Result (enriched or detail mode)

{
"jobId":"4370317193",
"title":"Senior Software Engineer",
"company":"Google",
"companyUrl":"https://www.linkedin.com/company/google",
"companyLogo":"https://media.licdn.com/dms/image/v2/C4D0BAQ...",
"location":"Mountain View, CA",
"postedDate":"2 weeks ago",
"jobUrl":"https://www.linkedin.com/jobs/view/4370317193",
"isActivelyHiring":true,
"salary":"$170,000/yr - $250,000/yr",
"applicantCount":"Over 200 applicants",
"description":"We are looking for a Senior Software Engineer to join our Cloud Platform team. You will design and build large-scale distributed systems, mentor junior engineers, and drive technical decisions across the organization. Requirements: 5+ years of experience in backend development, proficiency in Java, Go, or C++, experience with distributed systems and cloud infrastructure...",
"seniorityLevel":"Mid-Senior level",
"employmentType":"Full-time",
"jobFunction":"Engineering and Information Technology",
"industries":"Technology, Information and Internet",
"applyUrl":"https://careers.google.com/jobs/results/123456",
"scrapedAt":"2026-04-07T12:00:00.000Z"
}

:zap: Tips

• Use enrichDetails: true to get salary, description, and seniority data — search results alone only include title, company, and location
• Combine filters for targeted results — e.g., remote + full-time + past24h to find fresh remote full-time jobs
• LinkedIn caps results at ~1,000 per search query — use more specific keywords or filters to stay within this limit
• Use companyId to get all jobs from a specific company — find the company ID from their LinkedIn URL (it's the numeric ID in the page source)
• Sort by recent to get the freshest postings first — useful for monitoring new job openings
• Any LinkedIn job URL format works — full URLs, slug URLs, bare numeric IDs, and URLs with tracking parameters are all accepted
• Salary data availability varies — not all job postings include salary; enrichment extracts it when LinkedIn displays it on the detail page
• Rate limiting is handled automatically — the actor includes retry logic with exponential backoff for 429 responses

🔗 Other LinkedIn scrapers

• LinkedIn Profile Scraper — extract name, headline, experience, education, and articles from public profiles
• LinkedIn Ad Library Scraper — search LinkedIn's Ad Library by keyword, company, or payer
• LinkedIn Company Scraper — extract company data, employee counts, posts, similar companies, and full addresses