# LinkedIn Jobs Scraper — Job Listings & Contact Finder (`shanks0x0/linkedin-jobs-scraper`) Actor

Scrape LinkedIn jobs by keyword, location, or company. Extract titles, descriptions, salaries, requirements, and find company contact info for lead generation.

- **URL**: https://apify.com/shanks0x0/linkedin-jobs-scraper.md
- **Developed by:** [Meherab Hossain](https://apify.com/shanks0x0) (community)
- **Categories:** Jobs, Lead generation, Social media
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## LinkedIn Jobs Scraper — Job Listings & Contact Finder

Scrape LinkedIn jobs by keyword, location, or company. Extract titles, descriptions, salaries, requirements, and company contact info for lead generation.

### Features

- Search by keyword, location, or company
- Extract job title, company, location, description
- Salary information when available
- Job requirements and qualifications
- Company contact info extraction
- Multi-language support
- Proxy support for geo-targeting

### Input

| Field | Type | Required | Description |
|---|---|---|---|
| searchQuery | string | | Job search query |
| location | string | | Job location (city, state, country) |
| maxResults | integer | | Max job listings to scrape |
| extractEmails | boolean | | Extract company emails |

### Output

Each dataset item contains: jobTitle, company, location, description, salary, requirements, postedDate, jobUrl, companyEmail, companyWebsite.

### Pricing

Pay-per-event: $0.001 per job listing.

# Actor input Schema

## `keywords` (type: `array`):

Job titles or keywords to search (e.g. 'Software Engineer', 'Marketing Manager')

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

City, state, or country to search in (e.g. 'San Francisco', 'Remote', 'New York')

## `maxResults` (type: `integer`):

Maximum number of jobs to extract per keyword-location combination

## `datePosted` (type: `string`):

Filter jobs by posting date

## `jobType` (type: `string`):

Filter by employment type

## `findCompanyContacts` (type: `boolean`):

Extract company website and email from job listing details

## `proxy` (type: `object`):

Use Apify proxy to avoid LinkedIn rate limiting

## Actor input object example

```json
{
  "keywords": [
    "Software Engineer",
    "Data Scientist"
  ],
  "locations": [
    "Remote",
    "San Francisco"
  ],
  "maxResults": 50,
  "datePosted": "Past week",
  "jobType": "All",
  "findCompanyContacts": true,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

Jobs stored in default dataset

# 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 = {
    "keywords": [
        "Software Engineer",
        "Data Scientist"
    ],
    "locations": [
        "Remote",
        "San Francisco"
    ],
    "proxy": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("shanks0x0/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 = {
    "keywords": [
        "Software Engineer",
        "Data Scientist",
    ],
    "locations": [
        "Remote",
        "San Francisco",
    ],
    "proxy": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("shanks0x0/linkedin-jobs-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "keywords": [
    "Software Engineer",
    "Data Scientist"
  ],
  "locations": [
    "Remote",
    "San Francisco"
  ],
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call shanks0x0/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=shanks0x0/linkedin-jobs-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/9WP6tOhWV8i64IQSi/builds/rJCpreDgAPtroGzgb/openapi.json