LinkedIn Jobs Scraper – No Login, Full Details & Salary Data

LinkedIn Jobs Scraper collects public LinkedIn job postings by keyword and location, or from any LinkedIn job search URL you paste, and returns one clean row per job. No LinkedIn login, no cookies, no proxy are needed: it reads the same public guest listings a logged-out visitor sees. Every job comes back with the full description, seniority level, employment type, job function, industries, applicant count, salary range (when the employer publishes one) and a direct link. You pay only per job delivered: searches that return nothing cost nothing.

This LinkedIn jobs scraper is built for people who need LinkedIn jobs data in bulk without maintaining their own scraper: recruiters and sourcing agencies, job boards, HR analytics teams doing salary benchmarking, sales teams treating "companies hiring" as a buying signal, and AI/RAG builders who want structured, flat JSON that drops straight into an agent or a vector store.

What you get

One flat, camelCase row per job. Nothing is nested, so CSV, Google Sheets, n8n and LLM prompts all work without a transform step.

Field	Description
id	LinkedIn job posting id (4468253955)
title	Job title
company, companyUrl, companyLogo	Employer name, LinkedIn company page, logo image
location	As written on the posting (Stockholm, Stockholm County, Sweden, Denver Metropolitan Area)
workType	remote, hybrid or onsite when you filtered on work type, or when the listing itself says remote/hybrid; otherwise null (LinkedIn does not print it on public listings)
postedAt	Posting date, ISO 8601 (2026-09-18)
postedText	LinkedIn's relative wording (4 days ago)
salary	Salary text exactly as published ($113,000.00/yr - $143,000.00/yr)
salaryMin, salaryMax, salaryCurrency, salaryPeriod	Parsed from salary: numbers, ISO currency code (USD, EUR, GBP…) and year / month / hour; null when no salary is published
seniorityLevel	Entry level, Associate, Mid-Senior level, Director, Executive, Internship, Not Applicable
employmentType	Full-time, Part-time, Contract, Temporary, Internship, Volunteer
jobFunction, industries	LinkedIn's own classification (Analyst and Finance, Financial Services)
applicantsText, applicantsCount	140 applicants and the integer 140; Over 200 applicants becomes 200; "Be among the first 25" stays text only
description	Full job description as readable plain text with paragraphs and - bullets, ready for LLMs and full-text search
descriptionHtml	The same description with the original HTML formatting
applyUrl	The employer's external apply URL when LinkedIn exposes it to logged-out visitors; null otherwise (see Limits)
url	Canonical LinkedIn job URL, tracking parameters removed
query, searchLocation	The keyword (or pasted URL) and location that found this job
scrapedAt	ISO 8601 UTC timestamp of the run

The LinkedIn Jobs Scraper de-duplicates jobs across all your keywords in a run, so one posting that matches "data analyst" and "business analyst" appears once.

Input

The simplest way to scrape LinkedIn jobs is one keyword and one location. Everything else has sensible defaults (past week, sorted by date, 50 jobs per keyword, full details on).

{
  "searchQueries": ["data analyst", "financial analyst"],
  "location": "United States",
  "datePosted": "pastWeek",
  "workType": "remote",
  "experienceLevel": "midSenior",
  "jobType": "fullTime",
  "sortBy": "date",
  "maxJobsPerQuery": 200,
  "fetchJobDetails": true
}

Or paste LinkedIn URLs. Search URLs are parsed into the same filters (the URL's own f_WT, f_TPR, f_E, f_JT, geoId, sortBy win over the form fields), and single job URLs fetch just that job:

{
  "startUrls": [
    { "url": "https://www.linkedin.com/jobs/search/?keywords=python%20developer&location=Stockholm%2C%20Sweden&f_WT=2&f_TPR=r2592000" },
    { "url": "https://www.linkedin.com/jobs/view/4468253955" }
  ]
}

When startUrls is non-empty it is used instead of the keyword list.

Option	What it does
Search keywords	One search per line: titles, skills or company names, exactly as you would type them into LinkedIn.
Location	City, region or country in LinkedIn's spelling, e.g. London, England, United Kingdom, Germany, Remote.
Date posted	Any time / past month / past week / past 24 hours (LinkedIn's own filter).
Work type	Any / on-site / remote / hybrid.
Experience level	Internship, entry level, associate, mid-senior, director, executive.
Job type	Full-time, part-time, contract, temporary, internship, volunteer.
Sort by	Most recent (best for monitoring) or most relevant.
Maximum jobs per search	1 to 1,000 per keyword or URL.
Fetch full job details	On: opens every job for description, seniority, salary, applicants. Off: listing-only rows in a fraction of the time.
Parallel requests	3 by default. Lower it if the log shows rate-limit warnings.

Use cases

• Recruiters and sourcing agencies: pull every "Head of FP&A" opening in the Nordics posted this week, with applicant counts, and prioritise the ones with few applicants.
• Job boards and aggregators: keep a niche board fresh by running the LinkedIn Jobs Scraper for your vertical every morning, deduplicated by id, straight into your database.
• HR analytics and salary benchmarking: the parsed salaryMin / salaryMax / salaryCurrency fields turn published ranges into a dataset you can chart by title, seniority and city.
• Sales and lead generation: a company hiring three SDRs or a Salesforce admin is a buying signal. Group rows by company, join companyUrl to your CRM, and route to the right rep.
• AI agents and RAG: description is plain text with paragraphs and bullets, descriptionHtml keeps formatting, and rows are flat, so the output drops into a vector store, an MCP tool result or an LLM prompt without cleanup.
• Market and labour researchers: track demand for a skill ("Snowflake", "IFRS 17", "Rust") across countries and weeks; postedAt and scrapedAt make time series easy.
• Job seekers and career coaches: one run a day with datePosted: past24h and your filters, pushed to Slack or email through an Apify integration.

Pricing

Pay per event: one job event per job row written to the dataset. Searches that return no jobs, unreachable job pages and error rows are free. There is no actor-start fee and no feature is gated: full details, salary parsing, URL input and filters are all included at the same per-job price.

A run with fetchJobDetails on costs the same per job as a listing-only run; it just takes longer because every job page is opened.

Integrations

Every LinkedIn Jobs Scraper run's dataset is available as JSON, CSV, Excel or XML through the Apify API the moment the run finishes, and the actor works with every Apify integration: n8n, Make, Zapier, Google Sheets, Slack, webhooks, MCP and the Python / JavaScript SDKs. Typical patterns: a daily schedule that appends new remote jobs to a Google Sheet, an n8n workflow that scores each description with an LLM and posts matches to Slack, or an AI agent that calls this actor through the Apify MCP server to answer "who is hiring data engineers in Berlin this week?".

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("nourishing_courier/linkedin-jobs-scraper").call(run_input={
    "searchQueries": ["fp&a analyst"],
    "location": "Stockholm, Sweden",
    "workType": "remote",
    "maxJobsPerQuery": 100,
})
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], "|", job["company"], "|", job["salary"], "|", job["url"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('nourishing_courier/linkedin-jobs-scraper').call({
    searchQueries: ['python developer'],
    location: 'Germany',
    datePosted: 'past24h',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map(j => `${j.title} @ ${j.company} (${j.location})`));

curl

curl -X POST "https://api.apify.com/v2/acts/nourishing_courier~linkedin-jobs-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>&format=csv" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries": ["data engineer"], "location": "United Kingdom", "maxJobsPerQuery": 50}'

In n8n or Make, use the Apify node / module with actor nourishing_courier/linkedin-jobs-scraper, pass the JSON input above, and read the dataset items in the next step. To export LinkedIn jobs to Google Sheets, add the Apify → Google Sheets integration in Console and it runs on every schedule.

Limits, fair use and legality

• Public data only. This LinkedIn job scraper reads job listings that LinkedIn serves to visitors who are not logged in. It never uses your account, cookies or session, so there is nothing to get banned, and it does not touch profiles or private data. Job postings are published by employers to be found; still, use the data responsibly and respect employers' and LinkedIn's terms for your use case.
• About 1,000 jobs per search. LinkedIn stops paginating a search at roughly 1,000 results. For bigger pulls, split by location, date window, work type or seniority: ten narrower searches return far more unique jobs than one broad one.
• Rate limits from one IP. LinkedIn answers bursts with HTTP 429. The actor retries with exponential backoff, slows every worker down when one is throttled, and keeps a small random delay between job pages. A 50-job run with details takes about a minute. If you run many searches at once and see repeated throttling warnings, lower Parallel requests or enable a proxy in Advanced.
• Apply URL. LinkedIn currently hides most employers' external apply links behind a sign-in prompt for logged-out visitors. applyUrl is filled in whenever the public page exposes it and is null otherwise; url always takes you to the posting.
• Work type. Public listings do not print on-site/remote/hybrid, so workType is set from your filter (or from "Remote"/"Hybrid" in the title or location) rather than from a field LinkedIn does not expose.
• Empty searches are reported, not hidden. A keyword that finds nothing gets one row with an error explaining why, and a run that delivers no jobs at all fails, so a scheduled workflow notices.

FAQ

Can I scrape LinkedIn jobs without logging in?

Yes. This actor only uses LinkedIn's public job listings, the pages any visitor can open without an account. You do not provide credentials, cookies or a session, and nothing runs under your identity.

How many jobs can the LinkedIn Jobs Scraper return per run?

Up to 1,000 per keyword or pasted URL, which is LinkedIn's own ceiling for one search. Add as many keywords as you like in one run; results are deduplicated across them. Splitting a broad search by location or date is the way to collect tens of thousands of jobs.

Does it return the full job description and salary?

Yes. With Fetch full job details on (the default), every job is opened and you get the full description as plain text and HTML, seniority level, employment type, job function, industries, applicant count and the published salary range, parsed into salaryMin, salaryMax, salaryCurrency and salaryPeriod. Only employers who publish a range have salary data; the rest are null, never guessed.

Can I scrape remote jobs only?

Set Work type to remote, or paste a LinkedIn search URL that contains f_WT=2. Combine it with a country or "Worldwide" as the location to build a remote jobs feed.

Can I paste a LinkedIn job search URL?

Yes. Any linkedin.com/jobs/search/?... URL is understood, including its filters (f_TPR, f_WT, f_E, f_JT, geoId, sortBy). Single job URLs (linkedin.com/jobs/view/<id>) fetch that one job with full details.

Does it work with n8n, Make, Zapier and Google Sheets?

Yes. Use the Apify node or module with this actor, or the run-sync API endpoint shown above, and the flat rows map straight onto sheet columns and workflow fields. Schedules in Apify Console handle daily or hourly refreshes.

Can an AI agent use it through MCP?

Yes. Apify's MCP server exposes any actor as a tool; point your agent at this actor and it can search LinkedIn jobs on demand and receive the flat JSON rows as the tool result.

How is the LinkedIn Jobs Scraper priced?

The LinkedIn Jobs Scraper charges per job delivered, with no actor-start fee. Error rows, empty searches and pages that could not be fetched are not charged.

What happens when LinkedIn rate-limits the run?

The actor backs off exponentially and retries each request several times. If a page still fails, the job keeps its listing data and gets a warning; if a whole search is blocked you get an explanatory error row and the log tells you to lower parallelism or wait a few minutes.

Is scraping LinkedIn jobs legal?

The LinkedIn jobs scraper accesses only publicly available job postings, without login, the way a search engine does. How you use the data is your responsibility: check LinkedIn's terms and your local law, especially if you republish postings or combine them with personal data.