LinkedIn Job Details Scraper - No Login

Turn public LinkedIn job URLs or IDs into complete structured job records without a LinkedIn login or cookies. Paste one URL or a bulk list from alerts, spreadsheets, CRM notes, or another crawler and export titles, companies, locations, descriptions, criteria, applicant text, compensation text, application paths, and source URLs to JSON, CSV, Excel, webhooks, or an API.

Try one current job first

Open the current London data-engineer description Task to inspect an editable one-result input before running. It resolves a current public posting instead of depending on an expiring fixed job ID. Review the Dataset and free RUN_SUMMARY, then replace the starter search with your own URL or ID list.

Start in 30 seconds

Paste one public job ID or URL first. To test the Actor without finding an ID, leave the list empty; the starter resolves one current public job from LinkedIn's guest search using your role and location, then records that choice in RUN_SUMMARY.

{
  "jobUrlsOrIds": [],
  "starterSearchQuery": "software engineer",
  "starterSearchLocation": "United States",
  "maxResults": 1
}

The starter query and location are used only when jobUrlsOrIds is empty. A supplied invalid or expired ID is reported as a failed input and is never silently replaced.

Open the run's Dataset tab when it finishes. One valid input produces one enriched job row; invalid IDs and failed fetches are not presented as successful records.

Temporary rate limits and upstream errors use bounded retries. Invalid, expired, blocked, or incomplete job pages are recorded in the non-billable RUN_SUMMARY record instead of the paid dataset. One bad URL does not cancel other valid jobs in the same batch.

What one result looks like

The Dataset contains one row per complete public job. This shortened example shows the stable fields most recruiting and automation workflows use:

{
  "jobId": "1234567890",
  "title": "Data Engineer",
  "company": "Example Company",
  "location": "London, England, United Kingdom",
  "postedAt": "2 days ago",
  "jobUrl": "https://www.linkedin.com/jobs/view/1234567890",
  "description": "Full plain-text job description...",
  "salaryText": null,
  "easyApply": false,
  "applyUrl": "https://example.com/careers/1234567890",
  "seniority_level": "Mid-Senior level",
  "employment_type": "Full-time",
  "job_function": "Engineering",
  "industries": "Software Development",
  "detailEnriched": true
}

Missing fields remain null. The Actor does not invent salary, seniority, applicant counts, recruiter details, or application links when LinkedIn does not expose them publicly.

Use cases

• Enrich LinkedIn job URLs with full descriptions
• Monitor hiring signals for target accounts
• Build job market datasets for salary, skill, and location analysis
• Feed recruiting workflows, job boards, Airtable, Clay, HubSpot, or BI dashboards
• Convert LinkedIn job IDs from search results into detailed structured records
• Run scheduled checks on high-value roles, competitors, and account lists

Agent and automation workflows

Use this actor after a LinkedIn jobs search to turn saved job IDs, URLs, alerts, spreadsheets, CRM notes, or lead lists into structured job-detail rows. It is shaped for Make, Zapier, n8n, Clay, Airtable, Google Sheets, ATS enrichment, sales triggers, and AI agents that need job descriptions and criteria without scraping personal profile data.

Common automation patterns:

• Enrich newly discovered jobs with descriptions and criteria
• Monitor high-value companies for new roles and reposts
• Feed job descriptions into skill extraction, lead scoring, and market maps
• Convert LinkedIn job URLs from emails, alerts, or spreadsheets into JSON/CSV
• Build weekly hiring-intelligence reports for recruiters, sales teams, and analysts

Connect directly from ChatGPT, Claude, or another MCP client through https://mcp.apify.com/?tools=neuton/linkedin-job-details-scraper.

Output

Rows include job ID, title, company, location, posted date text, applicant count text, job URL, company URL, logo URL, plain and HTML descriptions, salary text when displayed, Easy Apply status, application URL and type, seniority level, employment type, job function, and industries. Missing public fields remain null; the Actor does not infer compensation, applicant counts, recruiter identities, or criteria.

SEO keywords

LinkedIn job details scraper, LinkedIn job description scraper, LinkedIn job URL scraper, LinkedIn job ID scraper, LinkedIn hiring intelligence, LinkedIn job enrichment API, LinkedIn job posting extractor, public LinkedIn jobs no login.

Choose the right LinkedIn jobs Actor

• Use LinkedIn Job Details Scraper for exact job IDs and URLs.
• Use LinkedIn Jobs Search Scraper to discover jobs by keyword and location first.
• Use LinkedIn Remote Jobs Intelligence, LinkedIn Salary Jobs Intelligence, or LinkedIn Easy Apply Jobs Scraper for pre-filtered workflow-ready rows.
• Need contract, freelance, temporary, or fixed-term roles? Open the one-result LinkedIn Contract Jobs Intelligence Task. Its maximum successful starter charge is $0.012, and every retained row includes the public evidence used for classification.
• Use LinkedIn Company Hiring Signals or LinkedIn Job Skills Demand Scraper for company and skill aggregates.

Pricing recommendation

This acquisition Actor costs $0.70 per 1,000 complete job-detail rows. You are charged for enriched dataset results, not for opening the Actor page or for invalid IDs recorded in RUN_SUMMARY. Validate one job first, then scale the input after confirming the output fields. Specialized LinkedIn intelligence Actors are priced higher because they add verification, classification, or aggregation.

Troubleshooting and common questions

Do I need a LinkedIn login, cookie, or account?

No. The Actor reads public LinkedIn job pages and guest search surfaces. It does not request or store LinkedIn credentials.

Why did my run succeed with fewer rows than inputs?

Open the run's RUN_SUMMARY record. Expired IDs, private or blocked pages, duplicates, and incomplete responses are listed under failedInputs or duplicatesSkipped; they are not emitted as paid Dataset rows.

Can I run one job before sending a large list?

Yes. Set maxResults to 1, or use the current one-result Task near the top of this page. Confirm the description and application fields in the Dataset before increasing the batch.

How should I automate recurring enrichment?

Pass new job IDs from a search Actor, alert, spreadsheet, or CRM. Deduplicate on jobId, keep the first batch small, and schedule only the cadence your workflow needs. Use RUN_SUMMARY for diagnostics instead of treating missing rows as valid jobs.

Responsible use

This actor only targets public job posting pages. Do not use the output for spam, unlawful discrimination, or platform abuse.