LinkedIn Jobs Scraper — Remote Jobs, 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 read "meet the hiring team" cards or recruiter profiles. When a job description names a contact person, that person's name, email address and phone number are replaced with [name removed] / [email removed] / [phone removed] (deterministic rules for contact lines and contact blocks in English, German and French postings, such as "please contact

Filter like on LinkedIn itself - Easy Apply, Under 10 applicants, distance, remote / hybrid / on-site, minimum salary, experience level, job type, title words and excluded companies - and run it on a schedule with Only jobs new since the last run to get a daily feed of new postings only. Every row also carries ready-to-filter columns: workplaceType, yearsExperienceMin, visaSponsorship, skills and applyType.

$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, Hybrid or On-site, read from the location (United States (Remote)), a title tag (Engineer (Remote)) or a fixed phrase in the description (this is a hybrid role, fully remote, on-site role). Absent when none of them says it; LinkedIn's public pages have no workplace-type field.
workplaceTypeSource	string	Where workplaceType was read: location, title or description.

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.
applyType	string	The same as text: easy_apply or external.
yearsExperienceMin	integer	Years of experience from the first "N years ... experience" sentence of the description (3+ years of experience = 3). Absent when the description names none.
visaSponsorship	boolean	false when the description rules sponsorship out (unable to sponsor, without sponsorship), true when it offers it (visa sponsorship available); absent when it says neither.
skills	array	Skills from a fixed list of about 100 (languages, frameworks, cloud, data, business tools, healthcare certifications) named in the title or description, e.g. ["Python", "SQL", "AWS"].
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.
workplaceType	array	all	remote, hybrid, on-site. Checked on every job (see below); jobs that state no workplace are left out.
easyApply	boolean	false	Easy Apply jobs only (applied by LinkedIn's search).
under10Applicants	boolean	false	Jobs with fewer than 10 applicants only (applied by LinkedIn's search).
minSalary	integer	-	Minimum yearly pay in the posting's currency (hourly x 2,080, monthly x 12). Jobs without a published pay range are left out. Checked on every job.
distance	integer	-	Radius in miles around a city in locations (LinkedIn uses 5, 10, 25, 50, 100).
titleIncludes / titleExcludes	array of strings	-	Keep only titles with one of these words / skip titles with any of them. Whole words, case-insensitive.
excludeCompanies	array of strings	-	Skip these companies (e.g. staffing agencies); whole words of the company name.
onlyNewSinceLastRun	boolean	false	For schedules: skip every job an earlier run already delivered (see below).
seenJobsStoreName	string	linkedin-jobs-seen	The named key-value store that remembers delivered jobs; one name per monitor.
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. Easy Apply, Under 10 applicants and distance are applied by LinkedIn's search itself (measured October 2026), so they cost nothing extra. Workplace type and minimum salary are ignored by LinkedIn's logged-out search, so they are checked on each job like experience level: workplace type against the workplaceType column, salary against the top of the published pay range. With exactly one of remote / hybrid chosen, that word is added to your keyword search too.

Title and company filters (titleIncludes, titleExcludes, excludeCompanies) are decided on the search results before any job page is fetched; skipped jobs cost nothing and do not count toward Maximum results.

Only new jobs on a schedule. With onlyNewSinceLastRun, every job the run delivers is remembered in a named key-value store on your Apify account (seenJobsStoreName, default linkedin-jobs-seen), and later runs skip those jobs on the search results, before any request or charge. Schedule the same input daily and each run returns only new postings; a run that finds nothing new ends successfully with "No new matching jobs" and costs only the start fee. Use one store name per monitor.

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)

The default memory is 512 MB since version 1.1.0 (cheaper small runs). The numbers below are from runs at 1,024 MB with the default datacenter proxy; at 512 MB the same 500-job run took 8 min 56 s instead of 4 min 21 s at the same cost, so give a big run 1,024 MB when you want it faster.

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 its own workplace-type, salary, experience-level and job-type filters and its sort order (results come in LinkedIn's relevance order; use Date posted for the newest jobs). The Actor checks those filters on each job page instead, which costs one request per job checked.
• workplaceType, yearsExperienceMin, visaSponsorship and skills come from fixed text rules, not from a LinkedIn field: a job whose description does not say it gets no value, and the workplace filter leaves such jobs out.
• If a job-page filter (experience level, job type, workplace type, minimum salary) matches none of the jobs checked (up to 20 per requested result), the run ends without results and is marked failed.
• Title and company filters apply to searches; jobs requested by URL or id are always returned.
• Member data is out of scope: no recruiter profiles or hiring-team cards. Contact-person names, emails and phone numbers written in descriptions are replaced with [name removed] / [email removed] / [phone removed].

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

• LinkedIn Company Scraper - use it to add website, industry, company size and headquarters for the companies behind the postings.
• LinkedIn Jobs Scraper — Hiring Leads with Emails - use it when you need recruiter or hiring-manager contact emails, not just the postings.
• ATS Jobs Scraper - 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.
• Indeed Scraper - use it for Indeed job postings in 22 countries with parsed salary ranges and full descriptions.
• Glassdoor Scraper - use it for Glassdoor job listings with company ratings and salary estimates.
• Google Jobs Scraper - use it to collect job postings that Google aggregates from many job boards in one search.

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.