LinkedIn Jobs Scraper — Job Postings API, No Login | $0.50/1k

What does LinkedIn Jobs Scraper do?

Get LinkedIn job postings as clean spreadsheet rows: job title, company, company page and logo, location, the date the job was posted, the pay range when the employer published one (parsed into salaryMin and salaryMax), seniority, employment type, job function, industries, applicant count, Easy Apply, and the full job description as plain text.

Type a keyword and a location - software engineer in United States, nurse in United Kingdom - or paste a LinkedIn job-search URL straight from your browser, and scrape LinkedIn jobs into JSON, CSV or Excel, or read them from the Apify API. It works as a practical LinkedIn jobs API for job boards, recruiters, analysts and AI agents: no LinkedIn account, no login, no cookies, nothing to install.

It reads only LinkedIn's public job postings, the same pages LinkedIn shows to anyone who is not signed in. It never logs in and never touches member profiles. It does not collect recruiter names, "meet the hiring team" cards, emails or phone numbers.

$0.50 per 1,000 jobs plus $0.005 per run, platform compute and proxy included. A 1,000-job run with full descriptions costs about $0.51.

Use cases for this LinkedIn jobs scraper

• Job board or aggregator. Schedule one search per keyword and city every morning with Date posted = Past 24 hours, and publish fresh postings with the full descriptionText, employmentType and seniority.
• Recruitment agency. Find the companies hiring for the roles you place: filter on companyName, location and postedAt, and see how many people applied (applicantCount) before you call.
• Sales prospecting. A company hiring five data engineers is buying data tools. Search by role and group the rows by companyName and companyUrl to build an account list with real hiring intent.
• Labour-market and salary research. salaryMin, salaryMax, salaryCurrency and salaryPeriod are parsed from LinkedIn's pay range, so you can chart pay by role, country or industries.
• Job seekers and career tools. Pull every entry-level posting for a skill from the past week into a spreadsheet and track what you applied to.
• AI agents and automations. Call it with {"keywords": ["python developer"], "locations": ["Berlin"]} from an MCP client, n8n, Make or Zapier and get structured rows back.

What data can LinkedIn Jobs Scraper extract?

One row per job posting. A job found by several of your searches is returned once (de-duplicated by jobId). The Overview table shows title, companyName, location, postedAt, salaryText, employmentType, seniority, applicantCount, url, companyUrl, searchKeyword, status and error.

Job and company

Field	Type	Description
jobId	string	LinkedIn's numeric job id, e.g. 4454133738.
url	string	Public job page, https://www.linkedin.com/jobs/view/<jobId>/.
title	string	Job title as posted.
companyName	string	Hiring company.
companyUrl	string	The company's LinkedIn page.
companyLogo	string	Company logo image URL.
location	string	Location as LinkedIn writes it: city, region, country or metro area.
workplaceType	string	Remote or Hybrid, only when LinkedIn writes it into the location; LinkedIn's public job pages have no workplace-type field, so it is usually absent.

Date, pay and applicants

Field	Type	Description
postedAt	string	Posting date, ISO 8601 (LinkedIn gives the day, so the time is midnight UTC).
postedText	string	LinkedIn's relative time, e.g. 2 weeks ago.
salaryText	string	Pay range exactly as shown, e.g. $117,000.00/yr - $234,000.00/yr. Only when the employer published one.
salaryMin / salaryMax	number	The range parsed to numbers.
salaryCurrency	string	ISO currency code: USD, EUR, GBP, CAD, INR, ...
salaryPeriod	string	hour, day, week, month or year.
applicantsText	string	e.g. Over 200 applicants, Be among the first 25 applicants.
applicantCount	integer	The number in applicantsText (Over 200 = 200).
benefits	array	LinkedIn's highlights on the search card, e.g. Actively Hiring.

Job details (with Fetch full job details on, the default)

Field	Type	Description
descriptionText	string	Full description as plain text, paragraphs and bullet points on their own lines.
descriptionHtml	string	The same as HTML, only with Also keep the description as HTML.
seniority	string	e.g. Entry level, Mid-Senior level, Director.
employmentType	string	e.g. Full-time, Part-time, Contract.
jobFunction	string	e.g. Engineering and Information Technology.
industries	string	The company's industries as LinkedIn lists them.
easyApply	boolean	true = LinkedIn Easy Apply, false = apply on the company's site.
isClosed	boolean	true when LinkedIn says the job no longer accepts applications.
applyUrl	string	External apply link, only on the few postings where LinkedIn shows it without sign-in.
descriptionError	string	Why the details of this job could not be read; the row still has the search-card data.

Search and row status

Field	Type	Description
searchKeyword	string	Keyword of the search that found the job.
searchLocation	string	Location of that search.
status	string	ok, not_found or error (below).
error	string	Reason when status is not ok.
scrapedAt	string	ISO 8601 time the row was written.

status	Meaning	Billed?
ok	A job posting.	Yes
not_found	LinkedIn answered, but has nothing: a search with no jobs, a deleted posting, a company name LinkedIn does not know.	No
error	LinkedIn could not be read after retries. error says why.	No

A run whose only rows are not_found ends as Succeeded: "no jobs for this search" is an answer, not a failure.

How to scrape LinkedIn jobs

1. Open the Actor and click Try for free.
2. Type one or more Job titles or keywords and Locations - or paste LinkedIn job-search URLs into LinkedIn job-search URLs.
3. Optional: pick filters (Date posted, Experience level, Job type) or restrict to companies by name or id.
4. Set Maximum results (the default 20 shows you the output in seconds).
5. Click Start, then open the Output tab or export the dataset as JSON, CSV, Excel, XML or HTML.

To automate it, use the API tab (Node.js, Python, curl) or add a Schedule.

Input

Field	Type	Default	Description
keywords	array of strings	-	Job titles or keywords; each one is a separate search.
locations	array of strings	-	Countries, regions or cities; each is searched separately. Empty = worldwide.
startUrls	array of strings	one example search	LinkedIn job-search URLs (all filters kept), job URLs or job ids. The example is skipped as soon as you fill in keywords, locations or companies.
datePosted	string	any	1h, 24h, week, month or any.
experienceLevel	array	all	internship, entry, associate, mid-senior, director, executive. Checked on every job's page (see below).
jobType	array	all	full-time, part-time, contract, temporary, internship, volunteer, other. Checked on every job's page.
companyNames	array of strings	-	Only jobs at these companies, matched to their LinkedIn page by name.
companyIds	array of strings	-	LinkedIn company ids (the f_C value in a search URL).
geoId	string	-	LinkedIn's place id, for ambiguous place names.
fetchDescription	boolean	true	Full job details (one extra request per job). false = search-card data only, much faster.
includeDescriptionHtml	boolean	false	Also return the description as HTML.
maxItems	integer	20	Stop after this many jobs across all searches.
maxItemsPerSearch	integer	-	Cap per single search, so one broad search cannot use up maxItems.
proxyConfiguration	object	Apify Proxy on	Datacenter proxy (included). Residential proxies are not needed.

Filters apply to every search, pasted URLs included. keyword, location and query are accepted as aliases, which helps AI agents.

How the filters work. LinkedIn's logged-out search applies the date and company filters itself. It ignores experience level and job type (we measured identical results with and without them), so the Actor reads each job's own "Seniority level" and "Employment type" and saves only the jobs that match; the ones that do not match are never saved or billed. When you pick exactly one level or type, its words (e.g. entry level, part-time) are also added to your keyword search so that LinkedIn ranks matching jobs first; searchKeyword still shows your own keyword. That takes one job-page request per job checked, so filtered runs are slower. Remote/hybrid and salary filters are not offered because LinkedIn ignores them and its public job pages do not show the workplace type; you can add remote to your keywords, and filter on salaryMin in the output.

Example input:

{
    "keywords": ["data analyst", "data engineer"],
    "locations": ["United States", "Canada"],
    "datePosted": "week",
    "experienceLevel": ["entry", "associate"],
    "maxItems": 500,
    "maxItemsPerSearch": 125
}

Output

A real row from a platform run (description shortened):

{
    "url": "https://www.linkedin.com/jobs/view/4454133738/",
    "status": "ok",
    "jobId": "4454133738",
    "title": "(USA) Senior, Software Engineer",
    "companyName": "Walmart",
    "companyUrl": "https://www.linkedin.com/company/walmart",
    "companyLogo": "https://media.licdn.com/dms/image/v2/D560BAQHZkPdlecGssw/company-logo_100_100/company-logo_100_100/0/1736779000209/walmart_logo?e=2147483647&v=beta&t=tWcWIFSyHtICTzTLIPiYeKCp21XucI-HWijZdWwYR-A",
    "location": "Sunnyvale, CA",
    "postedAt": "2026-09-11T00:00:00.000Z",
    "postedText": "2 weeks ago",
    "benefits": ["Actively Hiring"],
    "applicantsText": "101 applicants",
    "applicantCount": 101,
    "seniority": "Not Applicable",
    "employmentType": "Full-time",
    "jobFunction": "Engineering and Information Technology",
    "industries": "Retail",
    "salaryText": "$117,000.00/yr - $234,000.00/yr",
    "salaryMin": 117000,
    "salaryMax": 234000,
    "salaryCurrency": "USD",
    "salaryPeriod": "year",
    "easyApply": false,
    "descriptionText": "Position Summary...\n\nWhat you'll do...\n\nRole summary:\n\nAs a Senior Software Engineer, you will lead the delivery of scoped features and solutions by collaborating with cross-functional teams ...",
    "searchKeyword": "software engineer",
    "searchLocation": "United States",
    "scrapedAt": "2026-09-27T23:34:53.593Z"
}

A search with no jobs, and a company name LinkedIn does not know, look like this (free):

{
    "url": "https://www.linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search?keywords=astronaut&location=Vatican+City&f_TPR=r3600&start=0",
    "status": "not_found",
    "error": "No results for this page",
    "scrapedAt": "2026-09-28T00:10:04.221Z"
}

Speed and reliability (real runs)

All numbers are from runs on the Apify platform at the default 1,024 MB, with the default datacenter proxy.

Run	Jobs	Time	Requests	Failed
Default input (no arguments), 6 staging runs	20	5-18 s	22	0
3 US keyword searches, full details	300	79 s	345	0
12 searches in 12 countries (US, UK, DE, IN, CA, AU, FR, NL, BR, SG, ES, PL), full details	1,188	6 min 11 s	1,308	0 (99.9% on the first attempt)

With Fetch full job details off, a run needs one request per 10 jobs instead of one per job. LinkedIn throttles busy IP addresses; the Actor retries a throttled request from a fresh IP, so throttling costs seconds, not rows.

How much does it cost to scrape LinkedIn jobs?

Pay per event, platform compute and proxy included:

Event	Price
Actor start	$0.005 per run
Result (status: ok job)	$0.0005 per job ($0.50 per 1,000)

Examples: the default 20-job run costs $0.015; 1,000 jobs cost $0.505; 10,000 jobs $5.005. Rows with status not_found or error are never billed. Cap spending with Maximum results and the run's Max total charge; the Actor stops cleanly when either is reached.

Tips

• More than 1,000 jobs for one query: LinkedIn serves at most 1,000 results per search. Split it: several locations (states or cities instead of a country), several related keywords, or Date posted = Past 24 hours on a daily schedule.
• Put several keywords and locations into one run instead of many small runs; you pay the start fee once, and duplicates across searches are removed for you.
• Use maxItemsPerSearch to spread maxItems evenly over your searches.
• For exact companies use companyIds; companyNames takes LinkedIn's best match for the name (check companyName in the output).

Limitations

• LinkedIn serves at most 1,000 jobs per search (see Tips).
• LinkedIn does not return "no results" for a keyword it does not recognise; it shows related jobs instead. searchKeyword tells you which search found each row.
• Pay ranges exist only where the employer published one (about one job in ten in our test runs, more in the US, UK and EU).
• Most external apply links are behind LinkedIn's sign-in, so applyUrl is usually empty; easyApply tells you how to apply.
• postedAt has day precision. Jobs requested by URL (not found through a search) have postedText only.
• LinkedIn's logged-out search ignores the workplace-type (remote/hybrid), salary, Easy Apply and "under 10 applicants" filters, so they are not offered. Experience level and job type are checked on each job page instead, which costs one request per job checked.
• If an experience-level or job-type filter matches none of the jobs checked (up to 20 per requested result), the run ends without results and is marked failed.
• Member data is out of scope: no recruiter names, profiles, emails or phone numbers.

FAQ

Do I need a LinkedIn account, cookies or a proxy? No. The Actor reads LinkedIn's public job pages without logging in; the datacenter proxy it uses is included in the price.

Is it legal to scrape LinkedIn jobs? It collects only job postings that LinkedIn publishes to anonymous visitors, and no member data. You are responsible for how you use the data; read the notice below and LinkedIn's terms.

Why did I get fewer rows than Maximum results? Your searches had fewer jobs, jobs repeated across searches (each is returned once), or a per-search cap or the run's charge limit was reached. The run log says which.

Can an AI agent call it? Yes. With no input at all it returns 20 software engineer jobs in the United States in seconds. Agents can pass keywords/keyword, locations/location or query as plain strings, and every row says whether it is data (ok), an empty answer (not_found) or a failure (error).

How fresh is the data? Every run reads LinkedIn live; nothing is cached. Use Date posted = Past hour / 24 hours for a feed of new postings.

Does it get the company's website, size or employees? No, only what the job posting shows: company name, LinkedIn page and logo.

Related Actors

• ATS Jobs: Workday, Greenhouse, Lever, BambooHR - use it to read postings straight from a company's own applicant-tracking system.
• Dice Jobs Scraper - use it for US tech and IT job-board listings instead of LinkedIn.
• Workable Jobs Scraper - use it for roles hosted on company Workable career pages.
• XING Jobs Scraper - use it for Germany, Austria and Switzerland listings.
• LinkedIn Jobs Scraper — Hiring Leads with Emails - use it when you need recruiter or hiring-manager contact emails, not just the postings.

Legal and data-protection notice

This Actor extracts only job postings that LinkedIn publishes publicly to visitors who are not signed in. It does not log in, does not work around access controls, and does not extract member data such as names, profile links, e-mail addresses or phone numbers. Job descriptions are written by employers and can still mention a contact person; personal data is protected by the GDPR in the European Union and by other laws worldwide, so do not use such data without a legitimate reason. You are responsible for complying with LinkedIn's terms of service and applicable law when you use the extracted data.

This Actor is an independent tool. It is not affiliated with, endorsed by or sponsored by LinkedIn Corporation. LinkedIn is a trademark of LinkedIn Corporation; all trademarks belong to their respective owners.