# LinkedIn Jobs Scraper (`moving_beacon-owner1/linkedin-jobs-scraper`) Actor
Scrapes LinkedIn job listings by keyword and location without requiring login or cookies. Extracts job titles, companies, locations, posting dates, and job URLs for market research, recruiting, and job monitoring.
- **URL**: https://apify.com/moving\_beacon-owner1/linkedin-jobs-scraper.md
- **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community)
- **Categories:** Jobs, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $10.00 / 1,000 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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 (No Cookies, No Login)
Scrape **LinkedIn job listings** by keyword and location — no LinkedIn account, no session cookies, no ban risk. Get clean, structured job data ready for export to **JSON, CSV, or Excel**, or pull it via API into your own pipeline.
### What data does it extract?
For every job listing:
| Field | Example |
|---|---|
| `title` | AI Engineer |
| `company` | Xelix |
| `location` | London, England, United Kingdom |
| `jobUrl` | https://uk.linkedin.com/jobs/view/ai-engineer-at-xelix-4420486484 |
| `postedDate` | 2 weeks ago |
| `postedDateIso` | 2026-06-18 |
| `searchKeywords` | AI Engineer |
| `searchLocation` | London |
### Use cases
- **Job market research** — track demand for skills or roles across cities.
- **Recruiting intelligence** — see which companies are hiring for what, right now.
- **Competitor hiring signals** — monitor competitor job postings to infer strategy.
- **Job boards & aggregators** — feed fresh listings into your own product.
- **Career tools** — power alerts like "new remote Data Engineer jobs this week."
### Input
```json
{
"keywords": "AI Engineer",
"location": "London",
"maxJobs": 100,
"datePosted": "pastWeek",
"jobType": "F",
"workplaceType": "2",
"experienceLevel": "any",
"proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}
````
### Output
Results are stored in the run's default dataset. Download them from the Apify Console or fetch via API:
```
https://api.apify.com/v2/datasets/{datasetId}/items?format=json
```
Sample item:
```json
{
"title": "AI Engineer",
"company": "Xelix",
"location": "London, England, United Kingdom",
"jobUrl": "https://uk.linkedin.com/jobs/view/ai-engineer-at-xelix-4420486484",
"postedDate": "2 weeks ago",
"postedDateIso": "2026-06-18",
"searchKeywords": "AI Engineer",
"searchLocation": "London"
}
```
# Actor input Schema
## `keywords` (type: `string`):
Job title, skill, or keyword to search for, e.g. AI Engineer, Data Analyst, Marketing Manager.
## `location` (type: `string`):
City, region, or country, e.g. London, United States, Remote.
## `maxJobs` (type: `integer`):
Maximum number of job listings to scrape.
## `datePosted` (type: `string`):
Only return jobs posted within this time window.
## `jobType` (type: `string`):
Filter by employment type.
## `workplaceType` (type: `string`):
Filter by on-site, remote, or hybrid.
## `experienceLevel` (type: `string`):
Filter by seniority.
## `proxyConfiguration` (type: `object`):
Proxies to use. Residential proxies are strongly recommended to avoid rate limiting by LinkedIn.
## Actor input object example
```json
{
"keywords": "AI Engineer",
"location": "London",
"maxJobs": 50,
"datePosted": "any",
"jobType": "any",
"workplaceType": "any",
"experienceLevel": "any",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": "AI Engineer",
"location": "London",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("moving_beacon-owner1/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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": "AI Engineer",
"location": "London",
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("moving_beacon-owner1/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": "AI Engineer",
"location": "London",
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call moving_beacon-owner1/linkedin-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=moving_beacon-owner1/linkedin-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Jobs Scraper",
"description": "Scrapes LinkedIn job listings by keyword and location without requiring login or cookies. Extracts job titles, companies, locations, posting dates, and job URLs for market research, recruiting, and job monitoring.",
"version": "0.0",
"x-build-id": "EVy6W3nIVEQvM0bcp"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/moving_beacon-owner1~linkedin-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-moving_beacon-owner1-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/moving_beacon-owner1~linkedin-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-moving_beacon-owner1-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/moving_beacon-owner1~linkedin-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-moving_beacon-owner1-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"keywords",
"location"
],
"properties": {
"keywords": {
"title": "Search keywords",
"type": "string",
"description": "Job title, skill, or keyword to search for, e.g. AI Engineer, Data Analyst, Marketing Manager."
},
"location": {
"title": "Location",
"type": "string",
"description": "City, region, or country, e.g. London, United States, Remote."
},
"maxJobs": {
"title": "Maximum jobs",
"minimum": 1,
"maximum": 1000,
"type": "integer",
"description": "Maximum number of job listings to scrape.",
"default": 50
},
"datePosted": {
"title": "Date posted",
"enum": [
"any",
"pastMonth",
"pastWeek",
"past24Hours"
],
"type": "string",
"description": "Only return jobs posted within this time window.",
"default": "any"
},
"jobType": {
"title": "Job type",
"enum": [
"any",
"F",
"P",
"C",
"T",
"I"
],
"type": "string",
"description": "Filter by employment type.",
"default": "any"
},
"workplaceType": {
"title": "Workplace type",
"enum": [
"any",
"1",
"2",
"3"
],
"type": "string",
"description": "Filter by on-site, remote, or hybrid.",
"default": "any"
},
"experienceLevel": {
"title": "Experience level",
"enum": [
"any",
"1",
"2",
"3",
"4",
"5",
"6"
],
"type": "string",
"description": "Filter by seniority.",
"default": "any"
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Proxies to use. Residential proxies are strongly recommended to avoid rate limiting by LinkedIn.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```