# ⚡ Fastest LinkedIn Jobs Scraper (`veeronica/linkedin-jobs-scraper`) Actor
Scrape LinkedIn job listings by keyword and location, or paste a LinkedIn jobs search URL. Get titles, companies, salaries, full descriptions, seniority, employment type, and applicant counts as clean JSON, CSV, or Excel — no login, no API key, no coding.
- **URL**: https://apify.com/veeronica/linkedin-jobs-scraper.md
- **Developed by:** [Veronica](https://apify.com/veeronica) (community)
- **Categories:** Jobs, Lead generation, Automation
- **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 listings
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
LinkedIn Jobs Scraper **extracts job listings from LinkedIn** — title, company, location, posting date, salary, full description, seniority, employment type, and applicant count — and downloads them as **JSON, CSV, Excel, or XML**. It runs in the cloud, needs no coding, and **no LinkedIn login or API key**.
Try it right away: type what you're searching for and where, click **Start**, and watch the dataset fill up with structured job data.
### What data does it extract?
Each result is **one job listing**:
| Data | Details |
|---|---|
| 💼 **Job** | title, canonical LinkedIn URL, posting date, "time ago", and any badges (e.g. *Actively Hiring*) |
| 🏢 **Company** | nested `company` object: name, LinkedIn page URL, and logo |
| 📍 **Location** | where the job is based, as shown on LinkedIn |
| 💰 **Salary** | pay or salary range, when LinkedIn shows one |
| 📋 **Details** | seniority level, employment type, job function, and industries |
| 👥 **Applicants** | number of applicants (as a number and as LinkedIn phrases it) |
| 📝 **Description** | the full job description in both plain text and HTML |
### How do I scrape LinkedIn jobs?
1. **Say what you want** — enter *Search keywords* (a job title or skill) and a *Location*.
2. **Narrow it down** *(optional)* — filter by date posted, experience level, job type, remote/on-site, and distance.
3. **Set how many** — choose *Maximum jobs*, or use `0` for as many as LinkedIn returns (capped at ~1,000 per search).
4. **Click Start** — then download the results from the **Storage** tab in any format, or send them anywhere with integrations.
> Prefer to build the search on LinkedIn yourself? Open `linkedin.com/jobs` in a private/incognito window, apply your filters, copy the URL from the address bar, and paste it into **LinkedIn search URLs**. You can add several.
### Speed vs. detail
By default the scraper opens each job's page to collect the full description, seniority, employment type, industries, and applicant count. If you only need the essentials shown on the results list (title, company, location, date, and salary when present), turn off **Fetch full job details** for a much faster, lighter run.
### Input example
```json
{
"keywords": "software engineer",
"location": "United States",
"maxItems": 100,
"datePosted": "pastWeek",
"experienceLevel": ["entryLevel", "associate"],
"jobType": ["fullTime"],
"workplaceType": ["remote", "hybrid"],
"sortBy": "recent",
"scrapeCompanyDetails": true
}
````
You can also drive it entirely from pasted LinkedIn search URLs:
```json
{
"startUrls": [
{ "url": "https://www.linkedin.com/jobs/search/?keywords=product%20manager&location=United%20Kingdom&f_WT=2&f_JT=F" }
],
"maxItems": 200
}
```
### Output example (abridged)
```json
{
"id": "4412034983",
"title": "Software Engineer I",
"url": "https://www.linkedin.com/jobs/view/4412034983",
"company": {
"name": "Sony Interactive Entertainment",
"url": "https://www.linkedin.com/company/sony-interactive-entertainment-llc",
"logo": "https://media.licdn.com/dms/image/.../sony_interactive_entertainment_llc_logo"
},
"location": "Los Angeles Metropolitan Area",
"postedDate": "2026-06-11",
"postedTimeAgo": "2 days ago",
"salary": null,
"employmentType": "Full-time",
"seniorityLevel": "Not Applicable",
"jobFunction": "Engineering and Information Technology",
"industries": "Software Development, Consumer Services, and Entertainment Providers",
"applicantsCount": 200,
"applicantsText": "Over 200 applicants",
"benefits": ["Actively Hiring"],
"descriptionText": "Why Sony Interactive Entertainment? …",
"descriptionHtml": "Why Sony Interactive Entertainment?
…",
"scrapedAt": "2026-06-14T16:48:34.963Z"
}
```
### Input reference
| Field | Type | Description |
|---|---|---|
| `keywords` | string | Job title, skill, or company to search for. |
| `location` | string | City, state, country, or region. Leave empty to search worldwide. |
| `maxItems` | integer | Total jobs to return across all searches. `0` = no limit. Default `100`. |
| `datePosted` | string | `any`, `past24h`, `pastWeek`, or `pastMonth`. Default `any`. |
| `sortBy` | string | `relevance` (LinkedIn's default ranking) or `recent` (newest first). |
| `experienceLevel` | array | Any of `internship`, `entryLevel`, `associate`, `midSenior`, `director`, `executive`. |
| `jobType` | array | Any of `fullTime`, `partTime`, `contract`, `temporary`, `internship`, `volunteer`, `other`. |
| `workplaceType` | array | Any of `onSite`, `remote`, `hybrid`. |
| `radius` | integer | Search radius in miles around the location. |
| `companyIds` | array | Restrict to specific companies by numeric LinkedIn company ID (the `f_C` value). |
| `scrapeCompanyDetails` | boolean | Open each job page for the full description and details. Default `true`. |
| `startUrls` | array | LinkedIn job-search URLs to scrape, each with its own filters. |
| `proxyConfiguration` | object | Proxy settings. Apify Proxy is strongly recommended. |
### Why scrape LinkedIn jobs?
- **Job-market research** — track demand for roles, skills, and titles over time.
- **Recruiting & sourcing** — monitor who's hiring and how competitive each posting is.
- **Lead generation** — find companies actively hiring in your space.
- **Salary benchmarking** — gather pay ranges where they're disclosed.
### Pricing
This Actor uses **pay-per-event** pricing: a small fee when a run starts, plus a fee per job delivered. You only pay for the listings you actually receive — set *Maximum jobs* to control your spend.
### Notes
- A proxy (via Apify Proxy) is strongly recommended; LinkedIn rate-limits unproxied scraping and may temporarily block your IP.
- The scraper uses LinkedIn's **public** job pages — the same data anyone can see without logging in. It does not log in or access private data.
- LinkedIn caps any single search at roughly **1,000 results**. To pull more, split your search into narrower queries (by location, date, or job type) or supply multiple search URLs.
- Make sure your use of the data complies with LinkedIn's terms and applicable laws.
# Actor input Schema
## `keywords` (type: `string`):
The job title, skill, or company to search for — exactly what you'd type into LinkedIn's job search box (e.g. software engineer, registered nurse, product manager).
## `location` (type: `string`):
City, state, country, or region to search in (e.g. San Francisco, California, United States, Remote). Leave empty to search worldwide.
## `maxItems` (type: `integer`):
How many job listings to return in total (across all keywords and search URLs). LinkedIn caps any single search at about 1,000 results. Use 0 for no limit.
## `datePosted` (type: `string`):
Only return jobs posted within this time window.
## `sortBy` (type: `string`):
Most relevant uses LinkedIn's default ranking; Most recent returns the newest jobs first.
## `experienceLevel` (type: `array`):
Keep only jobs at these experience levels. Leave empty to include all levels.
## `jobType` (type: `array`):
Keep only jobs of these employment types. Leave empty to include all types.
## `workplaceType` (type: `array`):
Keep only jobs with these work arrangements. Leave empty to include all.
## `radius` (type: `integer`):
Search radius around the location, in miles. Only applies when a specific city or area is set. Leave empty for LinkedIn's default.
## `companyIds` (type: `array`):
Optional — restrict results to specific companies by their numeric LinkedIn company ID. Find an ID in a company's job-search URL (the f\_C value). One per line.
## `scrapeCompanyDetails` (type: `boolean`):
Open each job's page to also collect the full description, seniority level, employment type, job function, industries, and applicant count. Turn this off for a much faster, lighter run that returns only the basics shown on the results list (title, company, location, date, and salary when present).
## `startUrls` (type: `array`):
Optional — instead of (or in addition to) the fields above, paste full LinkedIn job-search URLs. Open linkedin.com/jobs in a private/incognito window, apply any filters you like, then copy the URL from the address bar. Each URL is scraped with its own filters.
## `proxyConfiguration` (type: `object`):
Proxies to route requests through. Apify Proxy is strongly recommended — LinkedIn rate-limits unproxied scraping.
## Actor input object example
```json
{
"keywords": "software engineer",
"location": "United States",
"maxItems": 100,
"datePosted": "any",
"sortBy": "relevance",
"scrapeCompanyDetails": true,
"proxyConfiguration": {
"useApifyProxy": true
}
}
```
# Actor output Schema
## `jobs` (type: `string`):
One row per job listing.
# 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": "software engineer",
"location": "United States",
"proxyConfiguration": {
"useApifyProxy": true
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("veeronica/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": "software engineer",
"location": "United States",
"proxyConfiguration": { "useApifyProxy": True },
}
# Run the Actor and wait for it to finish
run = client.actor("veeronica/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",
"location": "United States",
"proxyConfiguration": {
"useApifyProxy": true
}
}' |
apify call veeronica/linkedin-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=veeronica/linkedin-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "⚡ Fastest LinkedIn Jobs Scraper",
"description": "Scrape LinkedIn job listings by keyword and location, or paste a LinkedIn jobs search URL. Get titles, companies, salaries, full descriptions, seniority, employment type, and applicant counts as clean JSON, CSV, or Excel — no login, no API key, no coding.",
"version": "1.0",
"x-build-id": "suwiV0NhVLizEm06L"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/veeronica~linkedin-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-veeronica-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/veeronica~linkedin-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-veeronica-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/veeronica~linkedin-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-veeronica-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"keywords": {
"title": "Search keywords",
"type": "string",
"description": "The job title, skill, or company to search for — exactly what you'd type into LinkedIn's job search box (e.g. software engineer, registered nurse, product manager)."
},
"location": {
"title": "Location",
"type": "string",
"description": "City, state, country, or region to search in (e.g. San Francisco, California, United States, Remote). Leave empty to search worldwide."
},
"maxItems": {
"title": "Maximum jobs",
"minimum": 0,
"type": "integer",
"description": "How many job listings to return in total (across all keywords and search URLs). LinkedIn caps any single search at about 1,000 results. Use 0 for no limit.",
"default": 100
},
"datePosted": {
"title": "Date posted",
"enum": [
"any",
"past24h",
"pastWeek",
"pastMonth"
],
"type": "string",
"description": "Only return jobs posted within this time window.",
"default": "any"
},
"sortBy": {
"title": "Sort by",
"enum": [
"relevance",
"recent"
],
"type": "string",
"description": "Most relevant uses LinkedIn's default ranking; Most recent returns the newest jobs first.",
"default": "relevance"
},
"experienceLevel": {
"title": "Experience level",
"type": "array",
"description": "Keep only jobs at these experience levels. Leave empty to include all levels.",
"items": {
"type": "string",
"enum": [
"internship",
"entryLevel",
"associate",
"midSenior",
"director",
"executive"
],
"enumTitles": [
"Internship",
"Entry level",
"Associate",
"Mid-Senior level",
"Director",
"Executive"
]
}
},
"jobType": {
"title": "Job type",
"type": "array",
"description": "Keep only jobs of these employment types. Leave empty to include all types.",
"items": {
"type": "string",
"enum": [
"fullTime",
"partTime",
"contract",
"temporary",
"internship",
"volunteer",
"other"
],
"enumTitles": [
"Full-time",
"Part-time",
"Contract",
"Temporary",
"Internship",
"Volunteer",
"Other"
]
}
},
"workplaceType": {
"title": "Remote / on-site",
"type": "array",
"description": "Keep only jobs with these work arrangements. Leave empty to include all.",
"items": {
"type": "string",
"enum": [
"onSite",
"remote",
"hybrid"
],
"enumTitles": [
"On-site",
"Remote",
"Hybrid"
]
}
},
"radius": {
"title": "Distance (miles)",
"minimum": 0,
"type": "integer",
"description": "Search radius around the location, in miles. Only applies when a specific city or area is set. Leave empty for LinkedIn's default."
},
"companyIds": {
"title": "Company IDs (advanced)",
"type": "array",
"description": "Optional — restrict results to specific companies by their numeric LinkedIn company ID. Find an ID in a company's job-search URL (the f_C value). One per line.",
"items": {
"type": "string"
}
},
"scrapeCompanyDetails": {
"title": "Fetch full job details",
"type": "boolean",
"description": "Open each job's page to also collect the full description, seniority level, employment type, job function, industries, and applicant count. Turn this off for a much faster, lighter run that returns only the basics shown on the results list (title, company, location, date, and salary when present).",
"default": true
},
"startUrls": {
"title": "LinkedIn search URLs (advanced)",
"type": "array",
"description": "Optional — instead of (or in addition to) the fields above, paste full LinkedIn job-search URLs. Open linkedin.com/jobs in a private/incognito window, apply any filters you like, then copy the URL from the address bar. Each URL is scraped with its own filters.",
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Proxies to route requests through. Apify Proxy is strongly recommended — LinkedIn rate-limits unproxied scraping.",
"default": {
"useApifyProxy": true
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```