# LinkedIn Jobs Scraper (No Cookies) (`chirpy_polygon/linkedin-jobs-scraper`) Actor

Scrape LinkedIn job postings by title, location, company, workplace type and posting age. Export job title, company, location, posted date, applicants and direct job URL with no cookies or login.

- **URL**: https://apify.com/chirpy_polygon/linkedin-jobs-scraper.md
- **Developed by:** [Bhojraj Pilaniya](https://apify.com/chirpy_polygon) (community)
- **Security:** Full permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 job results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Jobs Scraper (No Cookies)

Scrape LinkedIn job postings by job title, location, company, workplace type, employment type, experience level and posting age. **No LinkedIn login, cookies, or account required.**

Export clean, deduplicated job records for recruiting pipelines, job boards, market research, competitor hiring analysis and n8n/Make/Zapier automations.

This Actor is unofficial and is not affiliated with LinkedIn.

### What you get

- Job title
- Company name and company LinkedIn URL
- Location
- Workplace type (onsite / remote / hybrid)
- Employment type (full-time, contract, internship, ...)
- Experience level
- Posted date
- Number of applicants (when LinkedIn shows it)
- Salary text (when LinkedIn shows it)
- Direct job URL
- Full job description text
- Deduplicated records with a stable job ID

### Popular use cases

- Build a live job feed for a niche role or region
- Track which companies are hiring for a specific role
- Competitor hiring-signal monitoring
- Recruiting lead generation (who is hiring = who is buying recruiting tools)
- Salary and demand research by location
- Feed new jobs into n8n, Make, Zapier, Google Sheets, Airtable or a CRM
- Job board or aggregator backfill

### Why this Actor

- No cookies or LinkedIn login needed
- Search multiple job titles and multiple locations in a single run
- Rich filters: workplace type, employment type, experience level, Easy Apply, under-10-applicants, posting age, sort order
- Deduplicates results across overlapping queries
- Clean normalized schema, ready for sheets and CRMs

### Input

| Field | Description |
| --- | --- |
| Job Titles / Search Queries | One query per row. Supports boolean operators. |
| Locations | One LinkedIn location per row. Use full names, e.g. `United Kingdom` (not UK). |
| Companies | Optional. Only return jobs from these companies (URL or name). Max 10. |
| Maximum Jobs | Optional cap per query and location. |
| Posted Within | Any time, past hour, 24 hours, week or month. |
| Workplace Type | onsite, remote, hybrid. |
| Employment Type | full-time, part-time, contract, temporary, internship, volunteer, other. |
| Experience Level | internship, entry level, associate, mid-senior level, director, executive. |
| LinkedIn Easy Apply Only | Only jobs with Easy Apply. |
| Under 10 Applicants Only | Only jobs with fewer than 10 applicants. |
| Sort By | Relevance or most recent. |

### Quick start

1. Enter one job title, e.g. `software engineer`.
2. Optionally add one location, e.g. `India`.
3. Set `Posted Within` to `Past week` to keep results fresh.
4. Run and export the dataset.

### Example input

```json
{
  "jobTitles": ["software engineer", "data engineer"],
  "locations": ["India"],
  "postedLimit": "week",
  "workplaceType": ["remote"],
  "maxJobs": 100
}
```

### Output example

```json
{
  "title": "Senior Software Engineer",
  "companyName": "Example Company",
  "companyUrl": "https://www.linkedin.com/company/example/",
  "location": "Bengaluru, Karnataka, India",
  "workplaceType": "Remote",
  "employmentType": "Full-time",
  "experienceLevel": "Mid-Senior level",
  "postedAt": "2026-10-30",
  "applicantsCount": 24,
  "salary": "₹25,00,000/yr - ₹40,00,000/yr",
  "jobUrl": "https://www.linkedin.com/jobs/view/1234567890/",
  "descriptionText": "We are hiring ..."
}
```

### Pricing and total cost

- This Actor charges **per saved job result** (see the Pricing tab for the current rate and plan discounts).
- It runs a paid no-cookie data source underneath; those source charges are passed through and disclosed separately.
- A small Actor-start fee can apply even when no job is saved.
- Dry Run writes a sample row only and does not trigger a result charge.

### Limits and result interpretation

- Results reflect publicly visible LinkedIn job postings at the time of the run.
- LinkedIn location text matching can be fuzzy: use full country names (`United Kingdom`, `United States`).
- `applicantsCount`, `salary` and `experienceLevel` are only present when LinkedIn displays them; they are not guaranteed.
- A `SUCCEEDED` run means the run finished. Always inspect the dataset before importing.

### Legal and platform note

Use this Actor responsibly and only for lawful purposes. Review LinkedIn terms and applicable privacy/data protection rules for your use case.

# Actor input Schema

## `dryRun` (type: `boolean`):

Preview only; returns a sample row instead of live data. No result event is intended; an Actor-start fee can still apply.

## `jobTitles` (type: `array`):

One search query per row. Supports boolean operators, e.g. software engineer, "data scientist" OR "ml engineer".

## `locations` (type: `array`):

One LinkedIn location per row. Use full country names, e.g. United Kingdom, not UK. Leave empty for worldwide.

## `companies` (type: `array`):

Optional: only return jobs from these companies. Provide LinkedIn company URLs or company names. Maximum 10.

## `maxJobs` (type: `integer`):

Optional cap on jobs collected per query and location. Leave empty to use the source default.

## `postedLimit` (type: `string`):

Only return jobs posted within this period.

## `workplaceType` (type: `array`):

Optional: onsite, remote, or hybrid.

## `employmentType` (type: `array`):

Optional: full-time, part-time, contract, temporary, internship, volunteer, other.

## `experienceLevel` (type: `array`):

Optional: internship, entry level, associate, mid-senior level, director, executive.

## `easyApply` (type: `boolean`):

Only return jobs with the LinkedIn Easy Apply option.

## `under10Applicants` (type: `boolean`):

Only return jobs with fewer than 10 applicants.

## `sortBy` (type: `string`):

Sort results by posting date or relevance.

## `sourceMaxTotalChargeUsd` (type: `number`):

Advanced safety cap for the underlying data collection run. Leave empty for an automatic cap based on your query count.

## `sourceWaitSecs` (type: `integer`):

Maximum time to wait for the underlying data collection run.

## Actor input object example

```json
{
  "dryRun": false,
  "jobTitles": [
    "software engineer"
  ],
  "locations": [],
  "postedLimit": "any",
  "easyApply": false,
  "under10Applicants": false,
  "sortBy": "relevance",
  "sourceWaitSecs": 1800
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `runSummary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "dryRun": false,
    "jobTitles": [
        "software engineer"
    ],
    "locations": []
};

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

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "dryRun": False,
    "jobTitles": ["software engineer"],
    "locations": [],
}

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

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "dryRun": false,
  "jobTitles": [
    "software engineer"
  ],
  "locations": []
}' |
apify call chirpy_polygon/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,chirpy_polygon/linkedin-jobs-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/QravbfCRV2jR3R58d/builds/n5bZKekwciu8Gum0t/openapi.json