🔍 LinkedIn Jobs Scraper — Skills, Salary & B2B Hiring Signals

Extract LinkedIn job listings by keyword + location — no login, no cookies, no manual URL building required. Returns fully structured data including parsed salary (min/max numbers), required skills array, easy-apply flag, applicant count, seniority level, and full job description.

The only LinkedIn jobs actor with a documented output schema — making it the best choice for AI agents (Claude, ChatGPT) and automated pipelines.

Export scraped data, run via API, schedule recurring runs, or integrate with other tools.

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Why This Actor?

Most LinkedIn scrapers either require you to manually build search URLs, return raw unstructured text, or cost 5-10x more per result. This actor is different:

• Simple input — just type your job title and location. No URL building in incognito windows.
• Multi-query + multi-location — run ["Software Engineer", "ML Engineer"] × ["New York", "London"] in one run
• Parsed salary — returns salary_min: 180000 and salary_max: 240000, not just a raw string
• Skills as array — required_skills: ["Python", "PyTorch"] for easy filtering
• B2B hiring signals — find companies actively hiring to power sales prospecting and competitive intel
• Built-in deduplication — cross-query runs never return the same job twice
• Full output schema — every field documented for AI agent compatibility

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Use Cases

For recruiters and talent teams: Aggregate open roles across companies and locations. Monitor competitors' hiring activity. Build sourcing pipelines for specific skill sets.

For B2B sales teams: Identify companies hiring for roles that signal budget and buying intent. Find hiring managers and decision-makers. Use job postings as warm outreach triggers.

For job seekers and market researchers: Track salary trends across roles and geographies. Analyze which skills are most in-demand. Compare remote vs on-site availability by location.

For developers and data teams: Feed structured job data into dashboards, CRMs, ATS systems, or AI pipelines. Schedule daily monitoring runs for specific searches.

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Input Parameters

Simple keyword search (recommended)

{
  "searchQueries": ["Software Engineer", "Product Manager"],
  "locations": ["San Francisco, CA", "Remote"],
  "maxResults": 100,
  "datePosted": "r604800"
}

This runs 4 searches: each query × each location. Results are automatically deduplicated.

Direct URL mode (advanced)

Open linkedin.com/jobs in an incognito window, apply your filters, copy the URL, and paste it here:

{
  "startUrls": [
    { "url": "https://www.linkedin.com/jobs/search/?keywords=data+scientist&location=New+York&f_E=4&f_WT=2" }
  ],
  "maxResults": 200
}

With filters

{
  "searchQueries": ["DevOps Engineer"],
  "locations": ["United States"],
  "maxResults": 50,
  "experienceLevel": ["4", "5"],
  "workType": ["2", "3"],
  "jobType": ["F"],
  "salaryBase": "100000"
}

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Output Fields

Each result is a JSON object with the following fields:

Field	Type	Description
job_id	string	LinkedIn's unique job ID
job_title	string | null	Full job title
company_name	string | null	Hiring company name
company_url	string | null	LinkedIn company profile URL
company_size	string | null	Employee count range
company_industry	string | null	Industry category
location	string | null	City, state, work arrangement
work_type	string | null	Remote / Hybrid / On-site
employment_type	string | null	Full-time / Part-time / Contract
seniority_level	string | null	Entry / Mid-Senior / Director etc.
salary_range	string | null	Raw salary string from LinkedIn
salary_min	number | null	Parsed minimum salary (USD)
salary_max	number | null	Parsed maximum salary (USD)
required_skills	string[]	Extracted skills list
is_easy_apply	boolean	True if LinkedIn Easy Apply is enabled
applicant_count	string | null	e.g. "142 applicants"
posted_at	string | null	Relative posting time
job_description	string | null	Full plain-text description
job_url	string	Direct link to the job posting
search_query	string | null	Query that found this job
scraped_at	string	ISO timestamp of extraction

Example output record

{
  "job_id": "3812749302",
  "job_title": "Senior Machine Learning Engineer",
  "company_name": "Anthropic",
  "company_url": "https://www.linkedin.com/company/anthropic",
  "company_size": "201-500 employees",
  "company_industry": "Artificial Intelligence",
  "location": "San Francisco, CA (Hybrid)",
  "work_type": "Hybrid",
  "employment_type": "Full-time",
  "seniority_level": "Mid-Senior level",
  "salary_range": "$200,000–$280,000/yr",
  "salary_min": 200000,
  "salary_max": 280000,
  "required_skills": ["Python", "PyTorch", "RLHF", "Distributed Systems"],
  "is_easy_apply": false,
  "applicant_count": "142 applicants",
  "posted_at": "2 days ago",
  "job_description": "We are looking for a Senior ML Engineer...",
  "job_url": "https://www.linkedin.com/jobs/view/3812749302/",
  "search_query": "Machine Learning Engineer",
  "source_url": "https://www.linkedin.com/jobs/view/3812749302/",
  "scraped_at": "2026-03-31T14:22:00.000Z"
}

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Cost & Performance

Pricing: $0.0005 per job result (PAY_PER_EVENT). No actor start fee.

Scenario	Jobs	Estimated Cost
Quick search	50	~$0.025
Standard batch	200	~$0.10
Large scrape	1,000	~$0.50
Daily monitoring (50/day)	1,500/month	~$0.75/month

Compare: the dominant competitor charges $0.001/result (2x more). Premium competitors charge up to $0.005/result (10x more).

Performance: ~25–50 jobs/minute depending on LinkedIn's response times and proxy routing. 50 jobs typically takes 2–4 minutes.

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Filters Reference

Filter	Values
datePosted	r86400 (24h), r604800 (week), r2592000 (month)
jobType	F (Full-time), P (Part-time), C (Contract), T (Temporary), I (Internship)
experienceLevel	1 (Intern), 2 (Entry), 3 (Associate), 4 (Mid-Senior), 5 (Director), 6 (Executive)
workType	1 (On-site), 2 (Remote), 3 (Hybrid)
salaryBase	40000, 60000, 80000, 100000, 120000

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Limitations

• LinkedIn limits each search URL to ~1,000 results. Use multiple search queries to get more.
• Salary data is only available on job postings where the employer has added it (typically 30–40% of postings in the US).
• Skills extraction requires LinkedIn to expose the skills section on the public job page. For some postings, skills will be empty.
• LinkedIn may show an auth wall on some requests. The actor retries with a fresh session when this happens.

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No Login Required

This actor operates entirely on LinkedIn's public job search pages, which are accessible without an account. No cookies, no session tokens, no LinkedIn credentials needed.

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Support & Feedback

Found a bug or want a new feature? Open an issue on this actor's page. We respond within 48 hours and typically ship fixes within a week.

Works great with our Google Jobs Scraper for cross-platform job market research.

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Changelog

v0.1 — Initial release. Keyword + location search, multi-query cross-product, full detail page extraction, salary parsing, skills extraction, PPE pricing.