LinkedIn Jobs Scraper: $0.50 per 1,000 jobs, no login

Get public LinkedIn job offers as clean, structured data: title, company, location, date posted, full description (plain text and safe HTML), seniority level, employment type, industries, applicants, salary when shown, apply type and, if you want them, the company's public details (industry, size, website, address, specialties, followers…).

Search with keywords + a location, or paste LinkedIn job search URLs. One item per job, no duplicates.

• Public data only. The actor reads the job pages LinkedIn shows to any logged-out visitor. No LinkedIn account, no login, no cookies, no CAPTCHA solving.
• No personal data fields. Recruiter / job poster names, photos and profile links are never collected. Job descriptions are delivered as the employer wrote them (see the FAQ).
• One price, everything included. $0.50 per 1,000 jobs, all included: description, criteria and company details are in the price. No start fee, no paid options.

Why this LinkedIn jobs scraper?

Measured on 2026-10-27, on the same LinkedIn search ("data engineer", Berlin, past week, 100 jobs with company details), run at the same moment with two of the most used LinkedIn jobs scrapers on Apify:

	This actor	curious_coder	valig
Jobs delivered	100	99	100
Same jobs as ours	–	99 of 99	100 of 100
Run time, 100 jobs with company details	78.6 s	137.2 s	10.1 s, without company details (75 s one hour earlier)
Items with a recruiter / poster name or profile link	0	16	16

• Same jobs as the others. On that search, every job the other two scrapers returned was also in our results.
• Faster with company details in our test: 100 jobs with company details in 78.6 s, against 137.2 s for curious_coder started at the same moment (one run each; LinkedIn's speed varies during the day). On a large search: 1,000 jobs with descriptions in about 225 s (one run, United States).
• No recruiter or employee fields. No recruiter, job poster or employee data is extracted, and there were 0 LinkedIn profile links in 2,220 benchmark jobs (descriptions included).
• Clean text + safe HTML. description is plain text with paragraphs and - bullets (no blank lines between bullets, no leftover HTML entities). descriptionHtml keeps only simple formatting tags (paragraphs, line breaks, lists, bold, italics, underline, headings, quotes), with no links and no attributes (0 tags with attributes in 2,220 jobs).
• Numbers ready to filter: applicants as min / max / exact, salary as min / max / currency / period, company size as min / max, members on LinkedIn, followers, founded year. ISO dates, plus the hour when LinkedIn gives it.
• No start fee. A 20-job run costs $0.01. You pay per delivered job, never more than your run's spending limit.
• Filters are free for what they reject. Jobs rejected by your filters and jobs that no longer accept applications are not delivered and not charged. Duplicates are never charged.
• Past LinkedIn's ~1,000 limit. A LinkedIn search shows at most about 1,000 positions. When a search reaches it, the actor also runs it on the past month, week and day (London test: 791 distinct jobs from the plain search, 2,010 with the date windows).
• Moving from another scraper? Its input names are accepted, and outputFormat adds its output field names next to ours (see the migration guide).

How to use it

1. Type keywords (job title, skill, company) and a location (city, region or country, as on LinkedIn), or paste one or more LinkedIn job search URLs (search on linkedin.com/jobs, copy the address bar).
2. Set Maximum jobs per search (0 = all the jobs LinkedIn shows).
3. Optional: filters, company details, HTML description.
4. Click Start, then download the results as JSON, CSV, Excel, XML or HTML, or fetch them through the API.

Input examples

Keywords + location

{
  "keywords": "data analyst",
  "location": "United Kingdom",
  "maxJobs": 200
}

Several keywords and locations (JSON input: every keyword is searched in every location)

{
  "titles": ["data engineer", "analytics engineer"],
  "locations": ["Berlin", "Munich"],
  "maxJobs": 100
}

LinkedIn search URLs (keywords, location, date posted and company filters of the URL are used)

{
  "searchUrls": [
    "https://www.linkedin.com/jobs/search?keywords=data%20engineer&location=Berlin&f_TPR=r604800"
  ],
  "maxJobs": 100,
  "includeCompanyDetails": true
}

Filters

{
  "keywords": "product manager",
  "location": "United States",
  "datePosted": "pastWeek",
  "contractTypes": ["F", "C"],
  "experienceLevels": ["4", "5"],
  "onlyWithSalary": true,
  "excludeRecruitingAgencies": true,
  "titleExclude": ["intern"],
  "maxJobs": 500
}

Filter	Applied by
datePosted (past 24 hours / week / month), companyIds	LinkedIn
contractTypes (employment type), experienceLevels, easyApply, onlyWithSalary, excludeRecruitingAgencies	this actor, on each job page
companyName, companyExclude, titleInclude, titleExclude	this actor, on the search list

LinkedIn does not apply employment type, experience level or Easy Apply to logged-out visitors, so the actor checks them on each job page. A filtered search reads more job pages and takes longer, but you pay only for the jobs that match.

Only new jobs (scheduled runs: each run delivers, and charges, only the jobs this search did not deliver before)

{
  "keywords": "data engineer",
  "location": "Berlin",
  "datePosted": "past24Hours",
  "onlyNewJobs": true,
  "maxJobs": 0
}

Each search keeps the job IDs it delivered (IDs only) in a key-value store of your own Apify account (linkedin-jobs-seen by default, seenJobsStoreName to choose another). Known jobs are skipped before their job page is read. With datePosted the list to read stays short; without it, a run may go deep into older jobs to fill maxJobs.

Input names of other scrapers (same run, written for another actor)

{
  "urls": ["https://www.linkedin.com/jobs/search?keywords=nurse&location=Toronto"],
  "limitPerSource": 50,
  "scrapeCompany": true
}

Output example

One item per job (illustrative values, description shortened). With company details on:

{
  "jobId": "4400000001",
  "jobUrl": "https://www.linkedin.com/jobs/view/4400000001",
  "title": "Senior Data Analyst",
  "companyName": "Northwind Analytics",
  "companyUrl": "https://www.linkedin.com/company/northwind-analytics",
  "companyId": "1234567",
  "companyLogo": "https://media.licdn.com/dms/image/v2/.../company-logo_100_100/...",
  "location": "London, England, United Kingdom",
  "postedAt": "2026-10-27",
  "postedAtTimestamp": "2026-10-27T08:00:00.000Z",
  "postedAtPrecision": "hour",
  "postedTimeAgo": "6 hours ago",
  "applicantsCount": 200,
  "applicantsCountMin": 201,
  "applicantsCountMax": null,
  "applicantsCountIsExact": false,
  "applicantsText": "Over 200 applicants",
  "seniorityLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "industries": "IT Services and IT Consulting",
  "salary": "£55,000.00/yr - £65,000.00/yr",
  "salaryMin": 55000,
  "salaryMax": 65000,
  "salaryCurrency": "GBP",
  "salaryPeriod": "year",
  "salarySource": "employer",
  "salaryAdditionalCompensation": null,
  "applyType": "external",
  "jobInsight": "Actively Hiring",
  "benefitsCount": null,
  "description": "About the role\n\nYou will turn our product data into decisions.\n\nWhat you will do:\n\n- Build dashboards for the product teams\n- Own the weekly business review\n- Work with data engineers on new pipelines",
  "descriptionHtml": "<p><strong>About the role</strong></p><p>You will turn our product data into decisions.</p><p><strong>What you will do:</strong></p><ul><li>Build dashboards for the product teams</li><li>Own the weekly business review</li><li>Work with data engineers on new pipelines</li></ul>",
  "companyIndustry": "IT Services and IT Consulting",
  "companySize": "501-1,000 employees",
  "companySizeMin": 501,
  "companySizeMax": 1000,
  "companyEmployeesOnLinkedIn": 742,
  "companyWebsite": "https://www.northwind-analytics.example",
  "companyDomain": "northwind-analytics.example",
  "companyHeadquarters": "London, England",
  "companyAddress": {
    "street": "1 Example Street",
    "city": "London",
    "region": "England",
    "postalCode": "EC1A 1AA",
    "country": "GB"
  },
  "companyCountry": "GB",
  "companyType": "Privately Held",
  "companyFoundedYear": 2009,
  "companySpecialties": ["Analytics", "Data engineering", "Business intelligence"],
  "companySlogan": "Data you can act on",
  "companyFollowers": 18450,
  "companyDescription": "Northwind Analytics helps retailers understand their customers.",
  "searchKeywords": "data analyst",
  "searchLocation": "London",
  "searchUrl": "https://www.linkedin.com/jobs/search?keywords=data+analyst&location=London",
  "scrapedAt": "2026-10-27T14:05:12.481Z"
}

The dataset has two ready-made views: Overview (the job table) and Companies (jobs with their company details).

Output fields

Field	Type	Description
jobId	string	LinkedIn job ID
jobUrl	string	Public job page (www.linkedin.com, no tracking parameters)
title	string	Job title
companyName	string	Company name
companyUrl	string	Company's LinkedIn page
companyId	string	LinkedIn company ID (usable in the companyIds filter)
companyLogo	string	Company logo URL
location	string	Job location as shown by LinkedIn
postedAt	string	Date posted, ISO YYYY-MM-DD
postedAtTimestamp	string or null	ISO time, rounded to the hour or minute, when LinkedIn gives it ("6 hours ago")
postedAtPrecision	string	day, hour or minute
postedTimeAgo	string	LinkedIn's relative text ("1 week ago")
applicantsCount	number or null	Applicants number shown by LinkedIn (200 for "Over 200")
applicantsCountMin / applicantsCountMax	number or null	Bounds ("Over 200" = 201 / null; "Be among the first 25" = 0 / 24)
applicantsCountIsExact	boolean or null	true when LinkedIn shows an exact number
applicantsText	string	LinkedIn's text ("97 applicants")
seniorityLevel	string	Internship, Entry level, Associate, Mid-Senior level, Director, Executive, Not Applicable
employmentType	string	Full-time, Part-time, Contract, Temporary, Internship, Volunteer, Other
industries	string	Job industries
salary	string or null	Pay range as shown
salaryMin / salaryMax	number or null	Pay range as numbers
salaryCurrency	string or null	ISO currency code (USD, EUR, GBP…)
salaryPeriod	string or null	year, month, week, day or hour
salarySource	string or null	employer when LinkedIn says the employer provided the range
salaryAdditionalCompensation	array or null	Extras listed with the pay (bonus, equity…)
applyType	string	easyApply (apply on LinkedIn) or external (on the company's site)
jobInsight	string or null	LinkedIn's note on the card ("Actively Hiring", "Be an early applicant")
benefitsCount	number or null	Number of benefits shown on the card
description	string	Full description, clean plain text (with includeDescription)
descriptionHtml	string	Same, as safe HTML (with includeDescriptionHtml)
companyIndustry	string	Company industry (with includeCompanyDetails)
companySize	string	Size as shown ("501-1,000 employees")
companySizeMin / companySizeMax	number or null	Size as numbers ("10,001+" = 10001 / null)
companyEmployeesOnLinkedIn	number or null	Members who list the company on LinkedIn
companyWebsite	string	Company website
companyDomain	string	Website domain (example.com)
companyHeadquarters	string	Headquarters as shown
companyAddress	object	street, city, region, postalCode, country
companyCountry	string	ISO country code of the address
companyType	string	Privately Held, Public Company, Nonprofit…
companyFoundedYear	number or null	Year founded
companySpecialties	array or null	Specialties list
companySlogan	string or null	Company tagline
companyFollowers	number or null	LinkedIn followers
companyDescription	string	Company "About" text
searchKeywords / searchLocation	string	The search that found the job
searchUrl	string	That search on LinkedIn
scrapedAt	string	ISO time of the scrape

Company fields appear only when includeCompanyDetails is on. With it on (200 jobs, Germany), industry was filled for 94.5 % of jobs, size 93.5 %, website 95 %, country 86.5 %. A missing value means the company page did not show it.

With includeDescription off, the actor reads only the search list: companyId, the applicants fields, seniorityLevel, employmentType, industries, salarySource, salaryAdditionalCompensation, applyType and the description fields are then null or absent, and salary comes from the search list only.

Run statistics (jobs per search, requests, blocks, timings) are saved in the run's key-value store as RUN_STATS.

Pricing

$0.50 per 1,000 jobs ($0.0005 per job), all included: description, criteria, salary and company details. No start fee, no paid option. You pay only for jobs delivered to your dataset; filtered-out jobs, closed jobs and duplicates are free, and the actor never goes beyond the spending limit you set for the run.

Price comparison, per 1,000 jobs, Starter plan tier, measured 2026-10-27 from the public Store pricing:

Actor	Per 1,000 jobs	Start fee per run	Paid options
This actor	$0.50	none	none, all included
curious_coder/linkedin-jobs-scraper	$1.00	$0.00005	none
valig/linkedin-jobs-scraper	$0.36	$0.0009	none
bebity/linkedin-jobs-scraper	$1.25	$0.00005	company & hiring-contact insights +$0.90, company website +$0.80
cheap_scraper/linkedin-job-scraper	$0.60	$0.005	AI job analysis +$0.50

Prices of other actors can change: check their Store pages.

Limits and FAQ

Do I need a LinkedIn account or cookies? No. The actor reads only what LinkedIn shows to logged-out visitors. It never logs in, never sends cookies and never gets around the sign-in page.

What is not available logged out?

• Workplace filter (on-site / remote / hybrid): LinkedIn ignores it for logged-out visitors, so the actor does not send it and says so in the log. Remote or hybrid is often written in the title or description.
• Sorting (most recent / most relevant): ignored by LinkedIn logged out; jobs come in LinkedIn's default order. Use datePosted for fresh jobs.
• External apply URL: the public page only says whether you apply on LinkedIn (Easy Apply) or on the company's site; the company's link is behind the sign-in, so applyType is given, not the URL.
• Job function: not shown on public job pages.

How precise is the date? postedAt is the day LinkedIn shows. For recent jobs LinkedIn also says "6 hours ago": the actor then fills postedAtTimestamp to the hour (7 % of jobs on an any-time search, 22 % on a past-week search).

How many jobs show a salary? Only those whose employer published one: 5 % (Germany, 200 jobs), 10.4 % (ten countries, 1,000 jobs) and 15.5 % (United States, 1,000 jobs) in our tests. onlyWithSalary keeps only those.

Is the description complete? Yes, delivered as the employer wrote it (100 % of benchmark jobs had one). It may contain the employer's own contact details (a hiring email address or phone number) when the employer put them in the text. The actor never extracts people's data into separate fields.

How many jobs can I get per search? LinkedIn shows at most about 1,000 positions per search (fewer distinct jobs, since its list repeats some jobs between pages). With splitSearch on (default), the actor also runs the search on the past month, week and day to reach more jobs, and removes duplicates. To go further, split by location, keywords or company.

How fast is it? About 225 s for 1,000 jobs with descriptions in our tests, 78.6 s for 100 jobs with company details. Speed varies with LinkedIn's load: the actor uses 18 parallel requests by default and never more than 6 requests per second, and slows down by itself when LinkedIn asks it to. This moderate rate is on purpose.

What if LinkedIn blocks a request? The actor retries with another IP, waits when LinkedIn asks, and reads a suspicious empty page again before treating it as the end of the list. In the 1,000-job benchmark, 0.3 % of responses were blocks and the run still delivered all 1,000 jobs.

Is there a free trial? Apify's free plan gives monthly platform credit you can use on this actor.

Is scraping LinkedIn legal? The actor collects only job data that LinkedIn shows publicly to logged-out visitors, and extracts no recruiter or employee data (descriptions are delivered as the employer wrote them). You are responsible for how you use the data, in line with the laws that apply to you (for example GDPR) and LinkedIn's terms.

Is this an official LinkedIn product? No. This actor is not affiliated with, endorsed by or sponsored by LinkedIn Corporation. "LinkedIn" is a trademark of LinkedIn Corporation and is used here only to describe the public website the job data comes from.

Integrations

• API: run the actor and get the items in one call:

  curl -X POST "https://api.apify.com/v2/acts/fit_melon~linkedin-jobs-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
    -H "Content-Type: application/json" \
    -d '{"keywords":"data analyst","location":"London","maxJobs":50}'
  

  Or use the Apify client for JavaScript or Python.
• Make, n8n, Zapier: use the Apify app / node, choose this actor and pass the same JSON input.
• Webhooks: get a call when a run succeeds or fails, to load the dataset into your system.
• Schedules: run the same search every hour or every day (for example with datePosted: "past24Hours") to follow new jobs. Turn on onlyNewJobs to get and pay only for jobs the search did not deliver before (or give skipJobIds yourself, Advanced section).
• Exports: JSON, CSV, Excel, XML, HTML, or straight to Google Sheets through the integrations.

Migration guide

Coming from another LinkedIn jobs scraper? In most cases you only change the actor ID in Make, n8n, Zapier or your code.

Input names accepted

Our field	Also accepted
searchUrls	urls, startUrls, searchUrl, url
keywords	titles, title, keyword
location	locations
maxJobs	count, rows, limit, limitPerSource, maxRowsPerUrl, maxItems, maxResults
datePosted	publishedAt (also LinkedIn codes r86400, r604800, r2592000)
contractTypes	contractType, jobType, jobTypes, employmentType, employmentTypes
experienceLevels	experienceLevel, seniorityLevel
easyApply	filterEasyApply
onlyWithSalary	requireSalaryInfo
companyIds	companyId
companyName	companyInclude, companyNames
titleExclude	jobTitleExclude
includeCompanyDetails	scrapeCompany, companyProfile, enrichCompanyData
proxyConfiguration	proxy

Values in words also work in the other scrapers' input names ("full-time", "contract", "entry level", "week"…). Known input fields of those scrapers that we do not support are named in the run log.

Output field names: outputFormat

Value	Adds next to our fields
auto (default)	detects the scraper your input was written for (from input names only it uses)
standard	nothing, our names only
curious_coder	id, link, companyLinkedinUrl, inputUrl, descriptionText, companyEmployeesCount; companyAddress is given in curious_coder's schema.org shape (streetAddress, addressLocality…) instead of ours
valig	id, url, postedDate, experienceLevel, contractType, workType and sector (the job industry), applicationsCount

Differences to check in your mappings: applicantsCount is a number here; applyType is easyApply / external. Recruiter / job poster fields of other scrapers are never delivered (they contain personal data).

Not affiliated with LinkedIn. LinkedIn is a trademark of LinkedIn Corporation.

Other actors by fit_melon

• Google Maps Scraper: businesses and places from Google Maps.

Feedback

Found a missing field or a wrong value? Open an issue on the actor's Issues tab with the run ID. It helps us fix it.