Scrape LinkedIn jobs without logging in

LinkedIn is the largest job board in the world, but its search pages are built for scrolling, not for analysis. If you want to track new roles every day, compare pay across cities or feed postings into your own job board, you need them as rows. This guide shows how to scrape LinkedIn job searches into JSON, CSV or Excel — without a LinkedIn account, cookies or a browser extension — for $1 per 1,000 jobs.

How it works (and what it doesn't do)

The tool reads the same public guest job pages that anyone sees on linkedin.com without signing in. It never logs in, never uses a session and never touches profiles or private data. The trade-off is that it sees what a logged-out visitor sees: LinkedIn caps any single search at roughly 1,000 results, and some fields (pay, applicant count) appear only when LinkedIn shows them publicly.

What you get

One row per job:

{
  "jobId": "4443948088",
  "url": "https://www.linkedin.com/jobs/view/senior-backend-software-engineer-gm-energy-at-general-motors-4443948088?position=10&pageNum=0&refId=XNLEHlnAq76tDxQ9kCrp5Q%3D%3D&trackingId=w737Jvl4M%2FyzMz2fkDf61Q%3D%3D",
  "title": "Senior Backend Software Engineer - GM Energy",
  "company": "General Motors",
  "companyUrl": "https://www.linkedin.com/company/general-motors?trk=public_jobs_jserp-result_job-search-card-subtitle",
  "location": "Warren, MI",
  "postedAt": "2026-09-26",
  "postedText": "2 weeks ago",
  "salary": "$129,400 - $198,400",
  "applicants": 200,
  "easyApply": false,
  "keyword": "software engineer",
  "searchLocation": "United States",
  "applyType": "external",
  "applyUrl": null,
  "description": "Job DescriptionThe Role:As a Senior Software Engineer focused on backend platform and API ownership, you will design, build, and operate scalable backend services that power critical product and business capabilities. You will be responsible for developing secure, reliable, an…",
  "descriptionHtml": "\n          <strong>Job Description<br><br></strong><strong>The Role:<br><br></strong>As a Senior Software Engineer focused on backend platform and API ownership, you will design, build, and operate scalable backend services that power critical product and business capabilities…",
  "seniority": "Not Applicable",
  "employmentType": "Full-time",
  "jobFunction": null,
  "industries": [
    "Motor Vehicle Manufacturing",
    "Appliances",
    "Electrical"
  ],
  "scrapedAt": "2026-10-11T15:35:06.185Z"
}

Step-by-step

1. Type what you are looking for in Keywords, such as data analyst. Run several searches in one job by separating them with semicolons: python; golang.
2. Set Location (Berlin, Austin, TX, Germany) or leave it empty for worldwide. Use Locations to repeat the same search in several places.
3. Narrow the results with Date posted (past24h, pastWeek, pastMonth), Work type (onsite, remote, hybrid), Experience level (the input field is experienceLevel: internship, entry_level, associate, mid_level, senior, manager, director, executive) and Job type (full-time, part-time, contract, temporary, internship, volunteer).
4. Set Max jobs for the whole run. Decide whether you need Include job descriptions: descriptions cost one extra request per job, so leave them off when titles and companies are enough.
5. Click Start and export to JSON, CSV or Excel.

Already have a search set up on linkedin.com with the filters you like? Paste its URL into Search URLs, and its keywords, location, date, work type, level and job type are applied for you.

Filter out the noise before you pay

Filters that run before a job is returned keep unwanted rows out of your dataset, and dropped jobs are not charged:

• Title includes (titleIncludes): keep only titles containing one of these words or phrases, such as ["data engineer", "analytics engineer"]. Matching is case-insensitive and on whole words.
• Title excludes (titleExcludes): drop titles containing words such as senior, staff or intern.
• Exclude companies (excludeCompanies): drop jobs from named companies, matched on the whole name.
• Apply on company site only (externalApplyOnly): return only jobs that send applicants to the company's own site. This costs one detail-page request per candidate job, so it is slower and a little more expensive.

{
    "keywords": "data engineer",
    "location": "Germany",
    "datePosted": "pastWeek",
    "experienceLevel": ["entry_level", "associate", "mid_level"],
    "titleExcludes": ["senior", "staff", "intern"],
    "excludeCompanies": ["Example Staffing Ltd"],
    "includeDescription": false,
    "maxJobs": 100
}

Run LinkedIn Jobs Scraper on Apify →

Call it from code

import json
import os
from apify_client import ApifyClient
client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("webdatatools/linkedin-jobs-scraper").call(run_input=json.loads("{\n    "keywords": "software engineer",\n    "location": "United States",\n    "datePosted": ""\n}"))
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('webdatatools/linkedin-jobs-scraper').call({
    "keywords": "software engineer",
    "location": "United States",
    "datePosted": ""
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

curl -X POST "https://api.apify.com/v2/acts/webdatatools~linkedin-jobs-scraper/run-sync-get-dataset-items" 
-H "Authorization: Bearer $APIFY_TOKEN" 
-H "Content-Type: application/json" 
-d '{"keywords":"software engineer","location":"United States","datePosted":""}'

Use it in n8n or Make

In n8n, add an HTTP Request node: method POST, URL https://api.apify.com/v2/acts/webdatatools~linkedin-jobs-scraper/run-sync-get-dataset-items, a header Authorization with the value Bearer YOUR_APIFY_TOKEN, and a JSON body such as the one above. The response is an array with one item per job. In Make, use the HTTP > Make a request module with the same method, URL and header, body type Raw with JSON content, and Parse response on. Then iterate over the returned array with an iterator.

Synchronous calls wait for the run to finish, so use them for small searches. For large searches, start the run asynchronously and read the dataset when it completes.

Download the n8n workflow (JSON) — a manual trigger, the HTTP Request node above and a placeholder for your token.

Recipes

Daily alert for new roles

Schedule a run each morning with Date posted set to past24h, your keywords and locations, and descriptions off. Send the new rows to Slack or email through Apify's integrations, n8n, Make or Zapier, and you get yesterday's postings without opening LinkedIn.

Compare a role across cities

Search one title with several entries in Locations, for example London, Manchester, Berlin and Amsterdam, and set Max jobs high enough to cover them. Group the results by searchLocation to compare volume, the seniority mix, applicants (competition) and, where published, salary.

Watch one company's openings

Open LinkedIn's job search, filter it to one company, copy the URL and paste it into Search URLs with Keywords left empty. Each run returns that company's current public postings. Compare jobId values from day to day to spot new and closed roles. For companies that use Greenhouse, Lever, Ashby or Workday, the Hiring Signals tool reads their own careers board, which is often more complete.

How much does it cost?

Primary event rates from a catalog snapshot; this is not the total price of a run. Additional charge events and Actor Start fees may apply; start fees can scale with memory. Check the Actor's Pricing tab on Apify for all events, conditions and current plan-specific rates, and set a maximum run budget before starting.

You pay per job returned; there is no separate charge for compute or proxies. Filtered-out jobs are not charged. Set Maximum cost per run and the Actor stops when the budget is used up.

How it compares

FAQ

Do I need a LinkedIn account?

No. The tool reads LinkedIn's public guest job pages, the same pages you can open in a private browser window without signing in.

Why do I get fewer than 1,000 jobs for a broad search?

LinkedIn caps each search at roughly 1,000 results. Split a broad search into narrower ones by location, date posted or experience level, and run them together: separate keywords with semicolons and list several locations.

Can I filter by salary?

Not in the input. Pay appears only when the posting states a range, and it is copied as written, so filter the salary column after the run. Postings with no stated range keep salary empty.

Why are salary and applicants empty on some jobs?

LinkedIn shows them only for some postings. When it does not display them publicly, the fields stay empty.

What happens if LinkedIn throttles requests?

In the default auto proxy mode the tool starts with direct requests and switches to Apify's residential proxy only when it is blocked. Use always to use the proxy from the start, or never to stay direct.

Is scraping LinkedIn jobs legal?

The tool collects publicly visible job postings only: no profiles, no private data and no login. You are responsible for how you use the data and for complying with LinkedIn's terms and local data-protection law (GDPR, CCPA) where you operate.