LinkedIn Jobs Scraper

What does LinkedIn Jobs Scraper do?

Search LinkedIn job listings by keyword and location, and get the results as structured data — job title, company, location, posting date, salary when shown, a link to apply, and the full job description.

No LinkedIn account, login, or cookie is needed. Type what you are looking for, press Start, and download the results as JSON, CSV or Excel — or pull them straight from the Apify API.

Why use LinkedIn Jobs Scraper?

• Track a job market — see what roles are being posted, where, and by whom.
• Build a job board — pull fresh listings for a niche and publish or share them.
• Watch competitors — see who is hiring, for what, and how fast they are growing.
• Recruiting research — compare titles, seniority and locations across many postings at once.
• Job hunting — collect every relevant opening into one spreadsheet instead of scrolling.

How to use LinkedIn Jobs Scraper

1. Enter your Search keywords, for example python developer.
2. Enter a Location, for example United States or Berlin, Germany. Leave it empty to search everywhere.
3. Set Maximum jobs to how many results you want.
4. Narrow things down with the filters if you like — date posted, job type, experience level, remote or on-site.
5. Tick Include full job description if you want the whole description text.
6. Click Start, then open the Output tab when it finishes.

Input

Field	Type	Required	Description
Search keywords (keywords)	string	Yes	What to search for.
Location (location)	string	No	Where to search. Empty means worldwide.
Maximum jobs (limit)	integer	No	How many jobs to return. Default 50.
Date posted (date_posted)	select	No	Any time, past 24 hours, past week, or past month.
Job type (job_type)	select	No	Full-time, part-time, contract, temporary, volunteer or internship.
Experience level (experience_level)	select	No	Internship through executive.
Workplace type (remote)	select	No	On-site, remote or hybrid.
Include full job description (include_description)	boolean	No	Adds the description, seniority, employment type, job function, industries and applicant count. Slower. Off by default.

Example input:

{
  "keywords": "python developer",
  "location": "United States",
  "limit": 25,
  "date_posted": "past week",
  "remote": "remote",
  "include_description": true
}

Output

One record per job:

{
  "job_id": "4451909310",
  "title": "Python Django Developer",
  "company": "Tata Consultancy Services",
  "company_url": "https://www.linkedin.com/company/tata-consultancy-services",
  "company_logo": "https://media.licdn.com/dms/image/v2/…",
  "location": "Morrisville, NC",
  "posted_at": "2026-08-11",
  "posted_relative": "5 days ago",
  "salary": null,
  "job_url": "https://www.linkedin.com/jobs/view/python-django-developer-at-tata-consultancy-services-4451909310",
  "description": "Job Description. Must have technical skills…",
  "seniority_level": "Not Applicable",
  "employment_type": "Full-time",
  "job_function": "Engineering and Information Technology",
  "industries": "IT Services and IT Consulting",
  "applicants": "Be among the first 25 applicants",
  "search_keywords": "python developer",
  "search_location": "United States"
}

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Data fields

Field	Description
job_id	LinkedIn's own id for the posting.
title	Job title.
company	Hiring company.
company_url	Link to the company's LinkedIn page.
company_logo	Company logo image.
location	Where the job is based.
posted_at	Date the job was posted.
posted_relative	The same date as LinkedIn shows it, e.g. "5 days ago".
salary	Pay range, when the employer published one.
job_url	Link to the posting, where you can apply.
description	The full job description. Needs Include full job description.
seniority_level	Seniority, e.g. Entry level, Mid-Senior level. Needs Include full job description.
employment_type	Full-time, contract, and so on. Needs Include full job description.
job_function	Job function, e.g. Engineering. Needs Include full job description.
industries	Industry of the hiring company. Needs Include full job description.
applicants	How many people have applied, when LinkedIn shows it. Needs Include full job description.
search_keywords, search_location	The search that produced this row, handy when you merge several runs.

What it cannot return

• Salary on every job. Most employers do not publish one, so salary is usually empty.
• Anything behind a login. Recruiter details, applicant lists and saved-job state are not public.
• Unlimited depth. A single search returns up to about a thousand jobs. For very broad searches, split them into narrower ones.

How much does it cost to scrape LinkedIn jobs?

Very little. Twenty-five jobs with full descriptions took about a minute and cost around a cent and a half. Twelve jobs without descriptions took seven seconds and cost well under a cent. Leaving Include full job description off is several times cheaper and faster.

Tips

• Narrow the search rather than raising the limit. Two searches split by location or job type will find more than one very broad search.
• Only tick Include full job description when you need the text — it is much slower and costlier with it on.
• Use Date posted for monitoring. Setting it to "past 24 hours" on a daily schedule gives you a clean feed of new postings with no duplicates to filter.

FAQ and support

Do I need a LinkedIn account or cookie? No. Job listings are public, and this Actor reads only what any visitor can see.

Why do some jobs have no salary? Because the employer did not publish one. LinkedIn shows a range only when it is provided.

Can I get more than a thousand results for one search? Not from one search — that is LinkedIn's own limit. Split it by location, job type or date range instead.

Is scraping LinkedIn legal? This Actor collects only publicly available data. You are responsible for how you use it, and you should not collect personal data without a legal basis. If in doubt, take legal advice.

Found a bug, or need a field that is not here? Open an issue on the Issues tab.

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