LinkedIn Jobs Scraper - Salary, Skills & Applicants

LinkedIn Jobs Scraper

Returns LinkedIn job postings as flat rows with 31 fields each: title, company, location, posted date, salary min and max, applicant count, benefits, full description, skills, seniority, employment type, job function and industry. No login, no cookies, no API key.

Measured reliability: 62 of 63 runs in the last 30 days succeeded (98.4%), 0 failed and 1 was aborted (Apify public run stats, 30-day window, read on 2026-09-24). A test run with the default input on 2026-09-24 returned 8 jobs with full details in 9.5 seconds.

LinkedIn's official API requires partner approval, OAuth tokens, and strict rate limits. This scraper reads the public job search pages directly. Keyword, location, company ID, date posted and Easy Apply go to LinkedIn's search. Job type, experience level, workplace type and minimum salary are checked by the Actor on each job page, because LinkedIn's logged-out search ignores them. It returns each match in one consistent schema, with optional full job descriptions and extracted skills.

Who uses it	What they scrape LinkedIn for
Recruiters	Monitor competitor hiring volumes and job descriptions for specific roles.
Job boards	Aggregate listings from LinkedIn into a centralized search index.
Market analysts	Track which skills and experience levels are in demand by region.
Sales teams	Find companies that are hiring to identify new business opportunities.

Common complaints about LinkedIn job scrapers, and how this one handles them

These come from 1 and 2 star reviews of other LinkedIn job scrapers on the Apify Store. Each answer below was checked against a real run or the source code.

Complaint	What this Actor does
Empty output, even after trying several inputs	The default input returned 8 full jobs on 2026-09-24. Over the last 30 days 62 of 63 runs succeeded and none failed.
Duplicate jobs in one run, each one charged again	Every job ID is kept in a set and written once per run. The 8 rows of the test run had 8 different job IDs, and the run charged exactly 8 results.
No company name in the output	company, companySlug, companyLinkedInUrl and companyLogo were filled on 8 of 8 rows in the test run.
Jobs posted weeks ago are shown with today's date	postedDate is read from the date LinkedIn prints on the listing, not from the time of the scrape. In the test run one job carried 2026-09-17 while the others carried 2026-09-24.
A keyword search returns a broad mix of job types	Job type, experience level, workplace type and minimum salary are checked on each job page, and only matching jobs are written and charged. In a test on 2026-09-24 a contract-only run returned 3 of 3 contract jobs, and a remote-only run returned 3 remote jobs after dropping 4 that did not match. Each row also carries jobFunction and industries.

What it does

This Actor collects LinkedIn job postings from a search query and location, and returns each one as a flat row with title, company, location, link, and optional full description, salary, skills, and raw HTML.

• 🔍 Search by title and location: Enter a job title or keyword and a city, state, country, or 'Remote'.
• 🏢 Company ID: Return only one company's jobs by its LinkedIn company ID.
• 📅 Date filters: Limit results to jobs posted in the past 24 hours, past week, or past month.
• 💼 Job type and experience: Keep only full-time, part-time, contract, internship and other types, and entry level through executive. Checked on each job page.
• 🏠 Workplace type: Keep only on-site, remote, or hybrid jobs, based on the workplace wording on each job page.
• ✅ Easy Apply only: Return only jobs that accept LinkedIn Easy Apply applications.
• 💰 Minimum salary: Keep only jobs with a published USD salary of at least $40k to $200k+ a year. Hourly and monthly pay are converted to yearly.
• 📄 Full job details: Fetch complete descriptions, company info, and salary data. This is on by default and is what fills the 31 fields.
• 🛠️ Skill extraction: Parse and return a list of skills mentioned in each job description.
• 📜 Raw HTML: Include the raw HTML of each job detail page for custom downstream parsing.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

Output fields

Every row has the same 31 fields. The fill counts come from the 8-job test run with the default input on 2026-09-24. Fields LinkedIn does not publish for a job come back as null.

Field	Type	Filled in test run	Description
id	string	8/8	LinkedIn job ID.
title	string	8/8	Job title.
company	string	8/8	Company name.
companySlug	string	8/8	Company handle in the LinkedIn URL.
companyLinkedInUrl	string	8/8	Company page on LinkedIn.
companyLogo	string	8/8	Company logo image URL.
location	string	8/8	Job location as LinkedIn shows it.
link	string	8/8	Job posting URL.
postedDate	string	8/8	Date the job was posted, YYYY-MM-DD.
postedDateRaw	string	8/8	Posted date as read from the listing.
salary	string	7/8	Short salary range, for example $165K - $225K.
salaryRaw	string	7/8	Salary text as LinkedIn prints it.
salaryMin	integer	7/8	Lower bound of the salary range.
salaryMax	integer	7/8	Upper bound of the salary range.
salaryCurrency	string	7/8	Currency code, for example USD.
salaryPeriod	string	7/8	year, month or hour.
salaryIsEstimate	boolean	7/8	True when the range is an estimate, not set by the employer.
applicants	integer	8/8	Applicant count. For "Be among the first 25 applicants" this is 25.
applicantsRaw	string	8/8	Applicant text as LinkedIn prints it.
benefits	array	8/8	Listed benefits, for example Dental, Vision, 401(k).
description	string	8/8	Full job description.
descriptionText	string	8/8	Description with whitespace cleaned.
descriptionLength	integer	8/8	Description length in characters.
skills	array	8/8	Skills found in the description.
workType	string	7/8	Remote, Hybrid or On-site.
experienceLevel	string	8/8	Seniority, for example Mid-Senior level.
employmentType	string	8/8	Full-time, Part-time, Contract and so on.
jobFunction	string	8/8	Job function, for example Engineering and Information Technology.
industries	string	8/8	Company industry.
searchQuery	string	8/8	The query and location that found the job.
scrapedAt	string	8/8	Time the row was collected, ISO 8601.

A real row from the test run (description shortened):

{
  "id": "4470016721",
  "title": "Software Engineer II, Backend (Identity Decisioning)",
  "company": "Affirm",
  "location": "St Louis, MO",
  "link": "https://www.linkedin.com/jobs/view/4470016721",
  "postedDate": "2026-09-24",
  "salary": "$165K - $225K",
  "salaryMin": 165000,
  "salaryMax": 225000,
  "salaryCurrency": "USD",
  "salaryPeriod": "year",
  "salaryIsEstimate": false,
  "applicants": 25,
  "applicantsRaw": "Be among the first 25 applicants",
  "benefits": ["Dental", "Vision", "Wellness"],
  "companyLinkedInUrl": "https://www.linkedin.com/company/affirm?trk=public_jobs_topcard_logo",
  "companySlug": "affirm",
  "descriptionText": "At Affirm, we exist for the moments that matter...",
  "descriptionLength": 4785,
  "skills": ["Python", "Kotlin", "AWS", "Kubernetes", "MySQL", "REST"],
  "workType": "Remote",
  "experienceLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "jobFunction": "Engineering and Information Technology",
  "industries": "Financial Services",
  "searchQuery": "software engineer United States",
  "scrapedAt": "2026-09-24T22:56:22.213Z"
}

What you can do with LinkedIn data

📊 Monitor hiring trends.

A market analyst runs the scraper weekly for 'data engineer' in 'United States' to track demand shifts and salary floors by region.

🎯 Build a niche job board.

A job board operator aggregates remote software roles by running daily scrapes for multiple tech titles and keeping the rows where workType is Remote.

📈 Prospect companies that are growing.

A sales team scrapes 'sales manager' in their target cities to identify companies with active hiring and reach out with a relevant pitch.

🧠 Analyze skill requirements.

An HR analyst extracts skills from 'product manager' postings across several regions to update internal competency models.

Why choose this scraper

	What you get
No login or cookies	Scrapes public LinkedIn job pages without authentication, so you never risk an account block.
Full detail mode	Optionally fetches the complete job description, company details, salary, and skills from each listing.
Fast basic mode	Disable full details to collect job IDs and links only, much faster. In a test on 2026-09-24 basic mode did not fill title, company or location, so keep full details on when you need those.
Rich filters	Narrow by keyword, location, company ID, date posted, Easy Apply, job type, experience level, workplace type and minimum salary. You pay only for jobs that match.

How it compares

This Actor offers full job detail scraping, skill extraction, and raw HTML output alongside the core search, while the alternative focuses on search results with company details.

Feature	ParseForge	Linkedin Jobs Search
Full job description scraping	Yes, optional	Not listed
Skill extraction from descriptions	Yes, optional	Not listed
Raw HTML output	Yes, optional	Not listed
Easy Apply filter	Yes	Not listed
Salary min and max in every row	Yes	Not listed
Workplace type filter (remote, hybrid, on-site)	Yes, checked on each job page	Not listed
Company ID filter	Yes	Not listed

Configure the run

Drive the Actor from a search query and location. The Input tab lists every parameter. Each example below is ready to paste into the JSON tab of the input.

1. First run with the defaults. Returned 8 full jobs in 9.5 seconds on 2026-09-24.

{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 10
}

2. Jobs posted in the last 24 hours. Returned 5 jobs, all posted 2026-09-24, in a test on that date.

{
  "searchQuery": "data engineer",
  "location": "United States",
  "maxItems": 50,
  "datePosted": "pastDay"
}

3. Contract jobs only. Returned 3 jobs on 2026-09-24, all with employmentType Contract.

{
  "searchQuery": "contract software developer",
  "location": "United States",
  "maxItems": 50,
  "jobType": ["contract"]
}

4. Remote jobs only. Returned 3 jobs on 2026-09-24, all with workType Remote. The Actor checked 7 jobs and dropped 4.

{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 50,
  "workplaceType": ["remote"]
}

5. One company's jobs by company ID. Returned 3 jobs on 2026-09-24, all from Google. To find an ID, filter by company on linkedin.com/jobs and copy the number after f_C= in the address bar.

{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 50,
  "companyId": ["1441"]
}

How the filters work: keyword, location, company ID, date posted and Easy Apply are sent to LinkedIn's search. LinkedIn's logged-out search ignores job type, experience level, workplace type, minimum salary and sort order, so the Actor applies those itself after reading each job page. When you filter on a field and a job page does not state it (for example no published salary, or seniority "Not Applicable"), that job is dropped. Dropped jobs are not charged. The run's status message says how many jobs were checked, kept and dropped. If fewer than 3% of the first 100 jobs checked match, the run stops early and says so, so you do not wait on a search that cannot fill your request. Most recent sorting is applied to the final results, which are then written at the end of the run.

Pricing

Pay per event. You pay only for jobs written to your dataset, plus a small start fee per run.

Event	Free plan	Top tier
Job returned	$0.00265	$0.002359
Run start	$0.001	$0.00089

Jobs collected	Approximate cost on the free plan
100 jobs	$0.27
1,000 jobs	$2.65
10,000 jobs	$26.50

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the LinkedIn Jobs Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to LinkedIn through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/linkedin-jobs-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your search query and location combination returns results on LinkedIn.com. Try broadening the location or removing restrictive filters like Easy Apply or a high minimum salary. A run that ends with 0 jobs is marked Failed, and its status message and log say why, including how many jobs each filter dropped.

Why are some jobs missing full details?

Some LinkedIn job postings block detail access. Enable 'Include Blocked Jobs' to still receive basic info for those listings with an isBlocked=true flag.

The scraper is running slowly. How can I speed it up?

Increase max concurrency, though this may raise the chance of blocks. Disabling 'Scrape Full Job Details' is faster but currently returns only job IDs and links.

I'm getting blocked or seeing empty results after many runs.

Reduce the max concurrency setting to a lower number, such as 5, to make requests less aggressive and avoid triggering LinkedIn's rate limits.

FAQ

Question	Answer
Do I need a LinkedIn account or API key to use this?	No. The scraper reads public LinkedIn job search pages and requires no login, cookies, or API credentials.
Can I scrape jobs from a specific company?	Yes, with Company ID. A company name in the search query is only a keyword and returns other employers too. Put the LinkedIn company ID in companyId instead: a test with 1441 returned only Google jobs.
How many jobs can I collect in one run?	You can set the maximum up to 1,000,000 jobs. The actual number returned depends on how many match your search and filters.
Will I get the same job twice in one run?	No. Each LinkedIn job ID is written once per run. A company that posts the same role in several cities has a separate job ID per city, so those appear as separate rows.
What is the difference between basic and full detail mode?	Full detail mode, the default, opens every job page and fills all 31 fields. Basic mode skips the job pages and currently returns the job ID and link only.
Can I filter by remote jobs only?	Yes. Set the workplace type filter to 'Remote'. The Actor reads the workplace wording on each job page and keeps only jobs that say remote; jobs with no workplace wording are dropped and not charged.
Does this scraper handle LinkedIn's anti-scraping measures?	The Actor runs on Apify's infrastructure with rotating proxies and configurable concurrency. Lower the max concurrency if you encounter blocks.
Can I get the raw HTML of each job page?	Yes. Enable the 'Include Raw HTML' option to receive the full HTML of each job detail page in your output for custom parsing.
How do I extract skills from job descriptions?	Enable the 'Extract Skills' option. The scraper will parse the job description and return a list of skills mentioned.
What export formats are supported?	You can export your dataset to CSV, JSON, Excel, or XML from the Apify platform.
Can I schedule this scraper to run daily?	Yes. Use Apify's scheduler to run the Actor at any interval, such as hourly or daily, to track new postings over time.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.