LinkedIn Jobs Scraper

Find, track, and enrich public LinkedIn job listings at scale for recruiting workflows.

Built for recruiting agencies and talent teams who need structured LinkedIn Jobs data for sourcing strategy, client reporting, and hiring trend analysis.

Why this actor

• Discover active openings by role, location, company, seniority, and job type.
• Spot hiring momentum quickly with repeatable, filterable data pulls.
• Extract salary and apply signals when available (fetchDetails=true).
• Capture dynamic job criteria and metadata for richer recruiter insights.
• Export clean JSON for ATS enrichment, CRM workflows, BI dashboards, and client deliverables.

Typical use cases

• Build targeted hiring maps for client requisitions.
• Identify companies scaling specific teams (engineering, product, sales, etc.).
• Benchmark salary visibility and role seniority across regions.
• Enrich ATS/CRM records with current hiring signals.
• Generate weekly talent market snapshots for clients.

Input parameters

Field	Type	Required	Description
keywords	String	Yes	Job title, skill, or other keyword to search for (example: Software Engineer).
location	String	Yes	Human-readable location (example: California, United States).
maxItems	Integer	Yes	Maximum number of jobs to return.
companyName	Array[String]	No	Company names to filter by. IDs are auto-resolved.
companyId	Array[String]	No	Company IDs to filter directly. Combined with resolved IDs from companyName.
publishedAt	String	No	Time window filter: "" (any), pastMonth, pastWeek, past24Hours.
workType	String	No	Workplace filter: "" (any), onSite, remote, hybrid.
contractType	String	No	Job type filter: "" (any), fullTime, partTime, contract, temporary, internship, volunteer.
experienceLevel	String	No	Seniority filter: "" (any), internship, entryLevel, associate, midSeniorLevel, director.
fetchDetails	Boolean	No	If true, visits each job detail page for richer fields (companyId, applyType, salary, applicants, descriptionText, criteria, metadata). Slower and uses more requests.

Example input

{
  "keywords": "Software Engineer",
  "location": "California, United States",
  "companyName": ["Google"],
  "publishedAt": "pastMonth",
  "workType": "onSite",
  "contractType": "fullTime",
  "experienceLevel": "midSeniorLevel",
  "maxItems": 50,
  "fetchDetails": true
}

Example output

The output includes core job fields, and when fetchDetails=true, it is enriched with salary, apply info, applicant counts, full text description, dynamic criteria, and metadata.

{
  "id": "4328991043",
  "title": "Software Engineer, Backend",
  "companyName": "Tinder",
  "companyId": "3517767",
  "companyUrl": "https://www.linkedin.com/company/tinder-incorporated",
  "location": "Los Angeles, CA",
  "jobUrl": "https://www.linkedin.com/jobs/view/software-engineer-backend-at-tinder-4328991043",
  "listedAt": "9 hours ago",
  "listedAtIso": "2026-03-19",
  "salary": "$160,000.00/yr - $180,000.00/yr",
  "applyType": "OFFSITE_APPLY",
  "criteria": {
    "seniorityLevel": "Not Applicable",
    "employmentType": "Internship",
    "jobFunction": "Engineering",
    "industries": "Software Development"
  },
  "metadata": {
    "payRangeSource": "Tinder",
    "featuredBenefits": ["Medical insurance", "Vision insurance"]
  }
}

Performance notes

• fetchDetails=false is fastest for broad monitoring.
• fetchDetails=true provides richer output but increases runtime and request volume.

Who is this for?

• Recruiting agencies managing multiple client searches.
• In-house talent acquisition teams monitoring competitor hiring.
• Talent intelligence and operations teams building data-driven recruiting workflows.

If your team needs reliable LinkedIn Jobs data to prioritize outreach and advise hiring strategy, this actor is built for you.

FAQ

Do I need cookies or login credentials?

No. This actor targets public LinkedIn Jobs guest endpoints.

Will new criteria fields appear automatically?

Yes. New label/value criteria are captured dynamically into criteria using camelCase keys.

Compliance and usage

You are responsible for using this actor in compliance with LinkedIn terms, local regulations, and your internal data-governance policies.