⚡️Rapid Linkedin Jobs Scraper

What does Rapid LinkedIn Jobs Scraper do?

Rapid LinkedIn Jobs Scraper is an Apify Actor that extracts public LinkedIn job listings (job titles, companies, locations, posting dates, salaries, full descriptions, seniority, employment type, applicant counts and more) without a LinkedIn login, cookies or account. Enter one or more job titles, choose a location, narrow the search with filters such as experience level, job type, remote / hybrid / on-site, posting date, company, city or Easy Apply, and download clean, structured data as JSON, CSV, Excel, XML, HTML, RSS or JSONL. You can also pull the results straight into your own app through the API.

It is a fast, affordable LinkedIn Jobs API alternative for recruiters, job boards, analysts, sales teams and AI agents that need fresh LinkedIn job data at scale. It is trusted by 15,000+ Apify users, starts at $0.10 per 1,000 jobs, and the monthly credits on Apify's Free plan cover up to 50,000 results every month.

At a glance

What it is	An Apify Actor that scrapes public LinkedIn job listings
LinkedIn account needed	No. No login, no cookies, no credentials
Search by	Job titles, location, cities, companies, experience level, job type, work arrangement, posting date, Easy Apply
Scrape modes	Quick (search-result data, fastest, $0.10 / 1,000 jobs) and Detailed (adds full job-page data, from $0.30 / 1,000 jobs)
Data you get	Title, company, company logo and link, location, posting date, hiring badges, salary, applicants, full description (text and HTML), seniority, employment type, industries, apply link, contact email
Export formats	JSON, CSV, Excel, XML, HTML table, RSS, JSONL
Ways to run	Apify Console, API, scheduler, webhooks, no-code integrations, MCP for AI agents
Pricing	Pay per result. Platform usage is free. Free monthly credits included

Why scrape LinkedIn job data?

LinkedIn is one of the largest professional job marketplaces in the world, so its public listings are a rich, up-to-date signal of who is hiring, for which roles, where, and at what pay. Teams use this scraper to turn those listings into data they can filter, chart, enrich and automate.

Recruiting and talent sourcing

Track new openings at target clients, spot companies that are scaling a team, and keep your own job pipeline fresh. The Actively Hiring and Early Applicant flags make it easy to prioritize roles that are worth acting on first.

Job boards and aggregators

Fill a niche job board, a newsletter or a career site with fresh listings. Run the scraper on a schedule, filter by title, location and posting date, and push only the new jobs into your database.

Labor-market and salary research

Measure demand for skills, compare roles across cities, watch remote-versus-on-site trends, and benchmark pay using the salary ranges that employers publish.

Sales and lead generation from hiring signals

A company that is hiring is a company that is spending. Find businesses hiring for roles that signal a need for your product or service (HR tech, recruiting, software, outsourcing, training) and build prospect lists from job data.

Competitive intelligence

Follow how competitors grow: which teams they expand, which locations they open, how fast they hire, and what seniority they look for.

AI agents and LLM applications

Give your AI assistant live job data. The Actor works with the Apify MCP server, so tools such as Claude, ChatGPT and Cursor can search LinkedIn jobs on demand. See Use LinkedIn job data with AI agents.

Job seekers and career coaches

Build a personal job-alert workflow: scrape the past 24 hours of roles that match your skills, export them to a spreadsheet and apply while the listing is still fresh.

Why use Rapid LinkedIn Jobs Scraper?

• ✅ No login required. Nothing to authenticate, no cookies to manage, no CAPTCHAs to solve, and no risk to your own LinkedIn account.
• ✅ Two scrape modes. Pick Quick for fast, low-cost listing data or Detailed for full job-page data. You pay only for the depth you need.
• ✅ Precise filters. Combine job titles, location, cities, companies, experience level, employment type, work arrangement, posting time and Easy Apply.
• ✅ Many searches in one run. Search several job titles, cities and companies together; the results are merged into a single dataset.
• ✅ Duplicate-free results. A job found by more than one search is returned only once.
• ✅ Freshness signals. Every job carries its posting date plus LinkedIn's hiring badges, so you can sort by recency and urgency.
• ✅ Proxies included. Proxy handling is built in. There is nothing to configure and no separate proxy bill.
• ✅ Pay per result, with a spending cap. You are charged for the jobs delivered, and the run stops as soon as your maximum cost per run is reached.
• ✅ Full Apify platform power. Scheduling, API access, webhooks, integrations, run monitoring and data storage are all included.

Rapid LinkedIn Jobs Scraper vs other ways to get LinkedIn job data

Approach	LinkedIn login needed	Risk to your account	Practical scale	Setup
Manual copy and paste	No	None	A few dozen jobs	Hours of repetitive work
Login-based scrapers and browser extensions	Yes (your account or cookies)	Account restrictions are possible	Medium	Install, log in, keep sessions alive
LinkedIn's official job APIs	Partner approval	None	Restricted to approved partners	Application and approval process
Rapid LinkedIn Jobs Scraper	No	None. It never touches your account	Large runs with multiple titles, cities and companies	Fill in a form and click Start

What data can you extract from LinkedIn jobs?

Every job comes back as one structured record. The data falls into six groups:

• Job basics: job ID, title, location and the direct LinkedIn job URL.
• Company: company name, LinkedIn company page and company logo.
• Freshness and hiring signals: posting date, relative posting time, and the Actively Hiring and Early Applicant badges.
• Compensation and competition: published salary range and the number of applicants.
• Job content: the full description as plain text and as raw HTML, plus seniority level, employment type and industries.
• Application details: the apply link, whether Easy Apply is available, and the first contact email found in the description.

Quick vs Detailed: which scrape mode should you choose?

The Scrape Mode input controls how much data is collected for each job. Both modes accept exactly the same search filters.

	Quick (quick)	Detailed (detailed, default)
Data collected	Everything shown on LinkedIn's job search results: title, company, location, posting date, hiring badges and job link	Everything in Quick, plus data from each job's own page: description, seniority, employment type, industries, applicants, salary and apply link
Speed	Fastest, because individual job pages are not opened	Slower, because every job page is opened
Price	$0.10 / 1,000 jobs	$0.30 to $0.35 / 1,000 jobs, depending on your Apify plan
Best for	Monitoring new postings, building alerts, counting and trend analysis	Lead generation, salary research, candidate matching, AI and NLP on job descriptions

How to scrape LinkedIn jobs (step by step)

1. Open the Actor on Apify Store and click Try for free (create a free Apify account if you don't have one).
2. Add your job titles (for example Software Engineer, Data Scientist). Each title is searched separately and the results are merged.
3. Set the location. Use a country, region or city such as United States, Europe, Remote or San Francisco, CA.
4. Choose a scrape mode (Quick or Detailed) and add optional filters: experience level, job type, work arrangement, posting time, companies, cities or Easy Apply.
5. Set how many jobs you want in Number of Jobs Entries (minimum 10).
6. Click Start. Results appear in the dataset while the run is still going.
7. Download your data from the Output tab as JSON, CSV, Excel, XML, HTML, RSS or JSONL, or fetch it through the API.

Example inputs

Remote Python jobs from the past week, with full details

{
  "jobs_titles": ["Python Developer", "Backend Engineer"],
  "location": "United States",
  "work_arrangement": "Remote",
  "posted_within": "Past Week",
  "jobs_entries": 500,
  "scrape_mode": "detailed"
}

New jobs at specific companies, from the last 24 hours (fast monitoring)

{
  "company_names": ["Stripe", "Shopify", "Atlassian"],
  "posted_within": "Past 24 hours",
  "jobs_entries": 200,
  "scrape_mode": "quick"
}

Data analyst jobs across several UK cities

{
  "jobs_titles": ["Data Analyst"],
  "location": "United Kingdom",
  "cities": ["London", "Manchester", "Birmingham"],
  "jobs_entries": 300
}

How much does it cost to scrape LinkedIn jobs?

Rapid LinkedIn Jobs Scraper uses pay-per-result pricing. Quick jobs cost $0.10 per 1,000 results on every plan, and Detailed jobs cost $0.35 per 1,000 results on the Free plan, falling to $0.30 per 1,000 on the Business plan. Apify platform usage is free, so there are no separate compute or proxy charges. You pay only for the jobs delivered to your dataset.

Result type	Free	Starter (Bronze, 4% off)	Scale (Silver, 5% off)	Business (Gold, 9% off)
Quick job	$0.10 / 1,000	$0.10 / 1,000	$0.10 / 1,000	$0.10 / 1,000
Detailed job	$0.35 / 1,000	$0.34 / 1,000	$0.32 / 1,000	$0.30 / 1,000

Cost examples

Jobs scraped	Quick	Detailed (Free plan)	Detailed (Business plan)
1,000	$0.10	$0.35	$0.30
10,000	$1.00	$3.50	$3.00
50,000	$5.00	$17.50	$15.00
100,000	$10.00	$35.00	$30.00

Is there a free plan?

Yes. Every Apify account on the Free plan gets $5 of free platform credits each month. With Quick mode that is up to 50,000 LinkedIn jobs per month for free, and about 14,000 jobs per month in Detailed mode. No credit card is needed to get started.

How do I stay in control of my spending?

Set a maximum cost per run in the run options. The Actor stops as soon as the limit is reached and keeps every result collected up to that point, so you never pay more than you planned.

For full pricing details, see the Pricing tab.

Input

Open the Input tab to configure a run. Only the fields you fill in are applied, so you can start with just a job title and a location. Here is the form, followed by what each field does:

🧾 Input fields

Title	ID	Type	Description
Job Titles	jobs_titles	List of strings	Job titles to search for, for example "Python Developer" or "Data Scientist". Each title is searched separately and the results are merged.
Location	location	String	A broad location such as Worldwide, Europe or Canada, or a full location string such as San Francisco, CA.
Cities (optional)	cities	List of strings	Specific cities to search, for example "London" and "Manchester". Set Location to the country so the cities are matched correctly.
Company Names	company_names	List of strings	Only return jobs from these companies. Use each company's name as it appears on LinkedIn for the best match.
Number of Jobs Entries	jobs_entries	Integer	How many jobs you want in this run (minimum 10, default 1,000).
Scrape Mode	scrape_mode	quick or detailed	How much data to collect for each job. detailed is the default. See Quick vs Detailed.
Experience level	experience	Select	Intern, Assistant, Junior, Mid-Senior, Director or Executive.
Job Type	employment_type	Select	Full-time, Part-time, Contract, Temporary, Volunteer, Internship or Other.
Work Schedule	work_arrangement	Select	On-site, Remote or Hybrid.
Job Posting Time	posted_within	Select	Any Time, Past 24 hours, Past Week or Past Month. If you set it, it takes priority over Custom Job Post Time.
Custom Job Post Time	job_post_time	String	A custom posting window in seconds, prefixed with r. For example r86400 is the past day and r172800 is the past two days. It is used only when Job Posting Time is not set.
Easy Apply Only	easy_apply	Boolean	Return only jobs that offer LinkedIn's "Easy Apply".

Good to know

• Company searches cover all regions by default. If you filter by company and leave Location empty, jobs are collected worldwide. Add a location to focus on one country.
• Existing integrations keep working. Older field names from previous versions (job_title, experience_level, job_type, work_schedule) are still accepted. For new integrations, use the fields in the table above.
• Every filter is optional. Leave a filter empty to include all values for it.

Output

Each run stores its results in an Apify dataset. You can download the dataset in various formats such as JSON, HTML, CSV, Excel, XML, RSS or JSONL, preview it as a table in the Output tab, or read it through the API.

📤 Output Fields

The Mode column shows which scrape mode returns the field. Fields that LinkedIn does not show for a particular job are returned as null.

Title	ID	Type	Mode	Description
Job ID	job_id	String	Quick, Detailed	Unique LinkedIn identifier of the job post.
Job URL	job_url	String	Quick, Detailed	Direct link to the job on LinkedIn.
Search Keyword	search_keyword	String	Quick, Detailed	The job title from your list whose search found this job.
Job Title	job_title	String	Quick, Detailed	Title of the position.
Company Name	company_name	String	Quick, Detailed	Name of the hiring company.
Company URL	company_url	String	Quick, Detailed	Link to the company's LinkedIn page, when available.
Company Logo URL	company_logo_url	String	Quick, Detailed	Direct URL of the company logo image.
Location	location	String	Quick, Detailed	Where the job is located.
Time Posted	time_posted	String	Quick, Detailed	How long ago the job was posted, for example "2 days ago".
Posted Date	posted_date	String	Quick, Detailed	Posting date in ISO format, for example 2026-09-24.
Hiring Badge	hiring_badge	String	Quick, Detailed	The badge LinkedIn shows on the listing, such as "Actively Hiring" or "Be an early applicant".
Actively Hiring	is_actively_hiring	Boolean	Quick, Detailed	true when the listing carries the "Actively Hiring" badge.
Early Applicant	is_early_applicant	Boolean	Quick, Detailed	true when the listing carries the "Be an early applicant" badge.
Apply URL	apply_url	String	Detailed	The link to apply. LinkedIn no longer exposes employers' external application links, so this is the LinkedIn job page, where the Apply button is.
Number of Applicants	num_applicants	String	Detailed	Current number of applicants, as shown by LinkedIn.
Salary Range	salary_range	String	Detailed	Salary or compensation, when the employer publishes it.
Job Description	job_description	String	Detailed	The full job description as plain text.
Job Description HTML	job_description_raw_html	String	Detailed	The full job description as raw HTML, with its original formatting.
Seniority Level	seniority_level	String	Detailed	The seniority level LinkedIn lists for the job.
Employment Type	employment_type	String	Detailed	Full-time, part-time, contract and so on.
Industries	industries	String	Detailed	The industries related to the job.
Easy Apply	easy_apply	Boolean	Detailed	Whether LinkedIn Easy Apply is available for the job.
Contact Email	contact_email	String	Detailed	The first email address found in the job description, if the poster included one.

🧪 Sample output

Tips for getting the best LinkedIn job data

• Start with Quick, then go deeper. Use Quick to discover and count jobs cheaply, then run Detailed when you need descriptions, salaries or applicant numbers.
• Collect larger volumes by widening the search. The number of jobs a search can return depends on how many public listings LinkedIn shows for it. To collect more, add several related job titles, list multiple cities, add company names, or leave filters such as experience level and job type empty.
• Monitor new jobs with a schedule. Combine Past 24 hours with a daily Apify schedule to receive only fresh postings.
• Match location to your goal. Use a country in Location with a list of Cities for city-by-city coverage, or a broad region such as Europe for wide coverage.
• Use exact company names. Company filters work best with the name exactly as it appears on the company's LinkedIn page.
• Use the Easy Apply filter to narrow quickly. It returns only jobs that support LinkedIn's one-click application.
• Cap your spend. Set a maximum cost per run, especially for large Detailed runs.
• Use results while the run is in progress. Jobs are added to the dataset as they are collected, so you can start using them before the run finishes.
• Expect empty fields for some jobs. Salary, applicant count and contact email only appear when the listing provides them.

Integrations, scheduling and API access

Schedule runs and get alerts

Run the scraper hourly, daily or weekly with Apify schedules, and trigger webhooks when a run finishes to notify your team or kick off the next step in your pipeline.

Connect LinkedIn job data to your tools

Send results to Google Sheets, Airtable, Slack, Make, Zapier, n8n and more using Apify's integrations. Build job alerts, CRM enrichment flows and reporting dashboards without writing code.

Run the scraper through the API

You can integrate the scraper directly into your database, app or automation pipeline with the Apify API. Replace YOUR_APIFY_API_TOKEN with your token from the Apify Console.

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_API_TOKEN' });

const input = {
    jobs_titles: ['Software Engineer', 'Data Scientist'],
    location: 'United States',
    work_arrangement: 'Remote',
    posted_within: 'Past 24 hours',
    jobs_entries: 100,
    scrape_mode: 'detailed',
};

// Run the Actor and wait for it to finish
const run = await client.actor('worldunboxer/rapid-linkedin-scraper').call(input);

// Fetch the results from the run's dataset
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Scraped ${items.length} LinkedIn jobs`);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

run_input = {
    "jobs_titles": ["Software Engineer", "Data Scientist"],
    "location": "United States",
    "work_arrangement": "Remote",
    "posted_within": "Past 24 hours",
    "jobs_entries": 100,
    "scrape_mode": "detailed",
}

# Run the Actor and wait for it to finish
run = client.actor("worldunboxer/rapid-linkedin-scraper").call(run_input=run_input)

# Fetch the results from the run's dataset
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["job_title"], "-", job["company_name"])

cURL

curl -X POST "https://api.apify.com/v2/acts/worldunboxer~rapid-linkedin-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"jobs_titles": ["Product Manager"], "location": "London", "jobs_entries": 50, "scrape_mode": "quick"}'

See the API tab of this Actor for ready-made code in more languages and the full API reference.

Use LinkedIn job data with AI agents (MCP)

Connect this scraper to your AI assistant through the Apify MCP server and let it search LinkedIn jobs on demand, with live data instead of stale training data.

🔗 Open the MCP configurator for Rapid LinkedIn Jobs Scraper

Works with: Claude Desktop, Claude.ai, Claude Code, Cursor, ChatGPT, Codex CLI, VS Code, Antigravity, Kiro and any other MCP-compatible client.

Example prompts you can try:

• "Find 50 remote Python developer jobs posted in the last 24 hours and summarize the salary ranges."
• "List companies in London that are actively hiring data analysts, and group them by industry."
• "Compare the number of senior product manager openings in Berlin, Amsterdam and Paris this month."

Frequently asked questions

Do I need a LinkedIn account or cookies to scrape LinkedIn jobs?

No. Rapid LinkedIn Jobs Scraper collects only the job information LinkedIn shows publicly to visitors who are not logged in. You never enter credentials or cookies, so your own LinkedIn account is never involved and cannot be restricted.

Is it legal to scrape LinkedIn jobs?

Collecting publicly available information is generally allowed in many jurisdictions, but the rules depend on your country, how you use the data, and LinkedIn's Terms of Service. Job listings can also contain personal data, which is regulated by laws such as the GDPR. This is not legal advice. See Legal and compliance below and consult a lawyer if you are unsure.

How much does the LinkedIn jobs scraper cost?

Quick jobs cost $0.10 per 1,000 results, and Detailed jobs cost from $0.30 per 1,000 results, depending on your Apify plan. Platform usage is free. See How much does it cost and the Pricing tab for details.

Can I scrape LinkedIn jobs for free?

Yes, within limits. Apify's Free plan includes $5 of platform credits every month, enough for up to 50,000 Quick results (about 14,000 Detailed results) each month, with no credit card required.

How many jobs can I scrape in one run?

Set the number you want in Number of Jobs Entries and the Actor collects up to that many unique jobs. The exact number depends on how many public listings LinkedIn shows for your search: a very narrow search has fewer jobs than a broad one. To collect large volumes, combine several job titles, cities and companies, and keep filters broad.

Which scrape mode should I use, Quick or Detailed?

Use Quick when listing-level data (title, company, location, posting date, hiring badges, link) is enough, for example to monitor new postings. Use Detailed when you need descriptions, seniority, employment type, industries, applicant counts, salary or contact email. Detailed is the default.

What data does the LinkedIn jobs scraper extract?

Job ID and URL, title, company name, company page and logo, location, posting date, hiring badges, salary range, number of applicants, full description (text and HTML), seniority level, employment type, industries, Easy Apply status, apply link and contact email. Quick mode returns the listing-level fields and Detailed mode returns all of them. See Output Fields.

Can I scrape LinkedIn jobs by company?

Yes. Add company names to Company Names and the scraper returns jobs posted by those companies. Combine it with a location, job title or posting-time filter to narrow the results.

Can I scrape jobs from several cities or countries at once?

Yes. Put the country in Location and list the cities in Cities, or use a broad region such as Europe or Worldwide. Results from every search are merged and de-duplicated.

Can I get LinkedIn salary data?

Yes, when the employer publishes it. In Detailed mode the salary_range field contains the compensation shown on the listing. Many LinkedIn jobs do not list a salary, and those return null.

Does it extract recruiter or contact emails?

In Detailed mode, contact_email contains the first email address found in the job description, when the poster included one. The Actor does not access private profiles or messages. Treat any email addresses as personal data and see Legal and compliance.

How can I monitor new LinkedIn jobs automatically?

Set Job Posting Time to Past 24 hours and run the Actor on a daily Apify schedule. Add a webhook or an integration to send the new jobs to Google Sheets, Slack, your database or your own app.

How fast is the scraper?

It is lightweight and does not rely on heavy browser automation. Quick mode typically returns hundreds of jobs in seconds. Detailed mode takes longer because it opens each job page, and larger runs scale accordingly.

Why did I get fewer jobs than I asked for?

The number of jobs available depends on how many public listings LinkedIn shows for your search. Narrow combinations of title, location and filters have fewer results. Try broader filters, a longer posting window, additional job titles, more cities, or a broader location.

Why are some fields empty?

Fields such as salary, applicant count and contact email are returned only when the listing provides them. Fields LinkedIn does not show for a job come back as null.

Can I export LinkedIn jobs to Excel, CSV or Google Sheets?

Yes. Download the dataset as Excel, CSV, JSON, XML, HTML, RSS or JSONL, or use the Google Sheets integration to send results to a spreadsheet automatically.

Can I use this with ChatGPT, Claude or other AI tools?

Yes. The Actor works with the Apify MCP server, so MCP-compatible tools such as Claude, ChatGPT and Cursor can run it directly. See Use LinkedIn job data with AI agents.

Is this a LinkedIn Jobs API alternative?

Yes. LinkedIn's official job APIs are limited to approved partners. Rapid LinkedIn Jobs Scraper gives you structured, programmatic access to public LinkedIn job data through the Apify API, with no partner approval and no LinkedIn account.

What happens if my run reaches its spending limit?

The Actor stops and keeps every result collected so far, so your dataset stays usable and you never pay more than the maximum cost per run you set.

Where can I report a problem or request a feature?

Open the Issues tab of this Actor, or use the contact details in Support and feedback. Bug reports and ideas are welcome.

Legal and compliance

This Actor is built to be ethical. It collects only information that LinkedIn shows publicly to visitors who are not logged in, and it does not access private profiles, messages or account data. We therefore believe it is safe to use for ethical purposes.

However, be aware that your results can contain personal data. For example, a job description may include a contact name or email address that the poster chose to publish (returned in contact_email). Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not collect or use personal data unless you have a legitimate reason to do so. If you are unsure whether your reason is legitimate, consult your lawyers.

LinkedIn's Terms of Service place restrictions on automated data collection. Review them and make sure your use case complies with them and with the laws that apply to you. You are responsible for how you use the data.

Rapid LinkedIn Jobs Scraper is an independent tool and is not affiliated with, endorsed by or sponsored by LinkedIn. LinkedIn is a trademark of its respective owner.

More job scrapers

Need job data from other sources? Try these Actors:

Actor	What it does
Rapid Indeed Jobs Scraper	Extract Indeed job listings from dozens of countries, with salaries, company profiles, contact emails, descriptions and apply links.
Dice Jobs Scraper	Extract job listings, company details, salaries and full job descriptions from Dice.com.

Support and feedback

Rapid LinkedIn Jobs Scraper is built and maintained by Umesh Patidar. If you like it, a review helps others find it. For bugs, ideas or custom requirements:

• Issues tab: report problems or request features directly on this Actor's page.
• Feedback form: https://forms.gle/HQyJGukRrCKmf2qF8
• Email: umeshpatidar.dev@gmail.com
• LinkedIn: Umesh Patidar