LinkedIn Jobs URL Scraper 💼🔗

Already have the job links? Paste them in and get back clean, structured JSON for every posting — full descriptions, company info, salary, job criteria and applicant counts. No keyword search, no login, no cookies.

✨ What you get

One record per job URL:

Field	Description
jobId / url / inputUrl	The job's id, its canonical LinkedIn URL, and the exact URL you submitted
title	Job title
companyName / companyUrl / companyLogo	The hiring company
location	Where the job is based
postedAt / postedTimeText	Posted date (derived to the day) + LinkedIn's "6 days ago"
salary	Salary when LinkedIn shows one
seniorityLevel / employmentType / jobFunction / industries	Job criteria
applicantsCount / applicantsText	How many people have applied
descriptionText / descriptionHtml	The full job description, plain text and HTML
scrapedAt	When the record was captured

⚙️ Options

• LinkedIn job URLs — one per line. Accepts any LinkedIn job link:
  • https://www.linkedin.com/jobs/view/4350364210
  • the full slug form, …/jobs/view/data-engineer-at-netflix-4350364210
  • a search/collection link carrying a job, …/jobs/search/?currentJobId=4350364210
  • or a bare job id, 4350364210
• Duplicate links (same job id) are scraped once.

🚀 Example

Input:

{
    "jobUrls": [
        "https://www.linkedin.com/jobs/view/4350364210",
        "https://www.linkedin.com/jobs/view/data-engineer-4317496119"
    ]
}

One record from the output:

{
    "jobId": "4350364210",
    "url": "https://www.linkedin.com/jobs/view/4350364210",
    "inputUrl": "https://www.linkedin.com/jobs/view/4350364210",
    "title": "Data Engineer (L5)",
    "companyName": "Netflix",
    "companyUrl": "https://www.linkedin.com/company/netflix",
    "companyLogo": "https://media.licdn.com/dms/image/v2/.../netflix_logo",
    "location": "United States",
    "postedAt": "2026-06-12T00:00:00.000Z",
    "postedTimeText": "6 days ago",
    "salary": null,
    "seniorityLevel": "Not Applicable",
    "employmentType": "Full-time",
    "jobFunction": "Other",
    "industries": "Entertainment Providers",
    "applicantsCount": 200,
    "applicantsText": "Over 200 applicants",
    "descriptionHtml": "<p>At Netflix, our mission is to entertain the world …</p>",
    "descriptionText": "At Netflix, our mission is to entertain the world …",
    "scrapedAt": "2026-06-18T02:05:45.000Z"
}

💡 Use cases

• Enrich a shortlist — turn a list of job links into a full spreadsheet of structured data.
• ATS / pipeline import — feed clean job records into your own systems.
• Monitoring — re-scrape saved job URLs to track applicant counts over time.
• Pair with search — collect job URLs elsewhere, then resolve them here in bulk.

💳 Pricing

You pay per job scraped — no subscriptions, no hidden compute costs. Free runs scrape up to 10 job URLs; paid members are unlimited (see FAQ).

❓ FAQ

Do I need a LinkedIn account or cookies? No. This scraper uses LinkedIn's public guest job pages — no login, password or session cookie.

What job URLs work? Any link that points to a specific job: the /jobs/view/<id> form (with or without the title slug), or a link with a currentJobId=<id> parameter. Links that don't contain a job id are skipped with a note in the log.

How accurate is postedAt? LinkedIn's public job page only exposes a relative time ("6 days ago"), so postedAt is derived to the day and postedTimeText keeps the exact wording.

Why was I limited to 10 jobs? Free runs are capped at 10 job URLs. You can still submit more, but only the first 10 are scraped and the run logs an upgrade notice. Upgrade your Apify plan to scrape unlimited URLs per run.