# LinkedIn Jobs Premium Scraper (`brilliant_gum/linkedin-jobs-premium-scraper`) Actor
Scrape LinkedIn job listings at scale — no account required. Full descriptions, salary ranges, applicant counts, seniority levels and 20+ fields per job. Advanced filters: Easy Apply, salary minimum, under 10 applicants, remote/hybrid. Cross-run deduplication included.
- **URL**: https://apify.com/brilliant\_gum/linkedin-jobs-premium-scraper.md
- **Developed by:** [Yuliia Kulakova](https://apify.com/brilliant_gum) (community)
- **Categories:** Jobs, Automation, Developer tools
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $25.00 / 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 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 Premium Scraper
**Scrape LinkedIn job listings at scale — no account required. Full descriptions, salary data, applicant counts and 20+ fields per job, ready to export.**
Search by keyword and location, apply powerful filters, and get clean structured data in minutes. Works out of the box without any LinkedIn login.
---
### What you get per job
| Field | Example |
|---|---|
| Job title | `Senior Product Manager` |
| Company name & LinkedIn URL | `Acme Corp` |
| Company logo | *(image URL)* |
| Location | `London, England, United Kingdom` |
| Date posted | `2026-05-12T00:00:00.000Z` |
| Salary range | `£85,000/yr – £95,000/yr` |
| Seniority level | `Mid-Senior level` |
| Employment type | `Full-time` |
| Job function | `Product Management` |
| Industries | `Software Development` |
| Applicant count | `42` |
| Apply method | `LinkedIn Apply` / `External` |
| Full description | *(HTML + plain text)* |
| Direct link | `linkedin.com/jobs/view/...` |
---
### Filters
| Filter | Options |
|---|---|
| **Date posted** | Any time · Past 24h · Past week · Past month |
| **Job type** | Full-time · Part-time · Contract · Temporary · Internship · Volunteer |
| **Experience level** | Internship · Entry · Associate · Mid-Senior · Director · Executive |
| **Work arrangement** | On-site · Remote · Hybrid |
| **Minimum salary** | $40K · $60K · $80K · $100K · $120K · $140K · $160K · $180K · $200K+ |
| **Easy Apply only** | One-click LinkedIn applications |
| **Under 10 applicants** | Fresh opportunities before the crowd |
| **Sort by** | Most relevant · Most recent |
---
### Premium features
**Cross-run deduplication** — tracks up to 200,000 job IDs across runs so you never scrape the same listing twice, even when running the same search daily.
**Location splitting** — LinkedIn limits results to ~1,000 per search. Enable location splitting to automatically break a country-wide search into city-level queries and collect far more results.
**Company details** — optionally enrich each job with company website, industry, employee count, headquarters, founded year and specialties.
**Auto cookie refresh** — provide your personal `li_at` cookie for extra stability. If it expires, the scraper refreshes it automatically — no manual work needed.
---
### Pricing
**$25 per 1,000 jobs** — pay only for results delivered.
| Volume | Cost |
|---|---|
| 100 jobs | ~$2.50 |
| 500 jobs | ~$12.50 |
| 1,000 jobs | ~$25.00 |
| 5,000 jobs | ~$125.00 |
---
### Example input
```json
{
"keywords": "product manager",
"location": "London",
"count": 100,
"datePosted": "pastWeek",
"workType": "remote",
"experienceLevel": "mid-senior",
"salary": "80000",
"scrapeJobDetails": true,
"sortBy": "date"
}
````
### Example output
```json
{
"id": "4376065576",
"title": "Senior Product Manager",
"companyName": "Acme Corp",
"companyLinkedinUrl": "https://www.linkedin.com/company/acme",
"companyLogo": "https://media.licdn.com/...",
"location": "London, England, United Kingdom",
"postedAt": "2026-05-12T00:00:00.000Z",
"postedAtTimestamp": 1747008000000,
"salaryInfo": "£85,000/yr - £95,000/yr",
"seniorityLevel": "Mid-Senior level",
"employmentType": "Full-time",
"jobFunction": "Product Management",
"industries": ["Software Development"],
"applicantsCount": 42,
"applyMethod": "LinkedIn Apply",
"descriptionText": "We are looking for a Senior PM to lead...",
"descriptionHtml": "We are looking for...
",
"link": "https://www.linkedin.com/jobs/view/4376065576",
"scrapedAt": "2026-05-15T10:00:00.000Z"
}
```
***
### Use cases
- **Job seekers** — track new openings matching your profile, set up daily runs
- **Recruiters** — monitor competitor hiring and market activity
- **HR & people analytics** — analyze salary trends and demand by skill or location
- **Sales teams** — identify companies actively growing in your target segment
- **Market research** — map hiring patterns across industries and regions
***
### FAQ
**Do I need a LinkedIn account?**
No. The scraper works fully without any login or cookie.
**How many jobs can I scrape per run?**
Up to 5,000. Use location splitting to collect even more for broad country-wide searches.
**Is salary data always available?**
Salary is shown only when the employer includes it. Roughly 30–50% of listings on LinkedIn include salary ranges.
**Can I run multiple searches at once?**
Yes — provide a list of direct LinkedIn search URLs in the `urls` field to run multiple searches in a single actor run.
**How fresh is the data?**
Scraped live from LinkedIn at the time of your run.
**What's the difference from the basic LinkedIn Jobs Scraper?**
This premium version adds salary filters, Easy Apply filter, Under 10 Applicants filter, location splitting, cross-run deduplication, company details enrichment, and cookie support — all in one actor.
# Actor input Schema
## `urls` (type: `array`):
LinkedIn job search URLs. If provided, overrides keywords/location params.
## `keywords` (type: `string`):
Job search keywords (e.g., 'software engineer')
## `location` (type: `string`):
Location filter (e.g., 'New York', 'London')
## `geoId` (type: `string`):
LinkedIn geographic ID for precise location filtering
## `count` (type: `integer`):
Maximum number of job results to scrape
## `datePosted` (type: `string`):
Filter by posting date
## `jobType` (type: `string`):
Filter by employment type
## `experienceLevel` (type: `string`):
Filter by experience level
## `workType` (type: `string`):
Filter by workplace type
## `sortBy` (type: `string`):
Sort results by relevance or date
## `easyApply` (type: `boolean`):
Only show jobs with LinkedIn Easy Apply
## `under10Applicants` (type: `boolean`):
Only show jobs with fewer than 10 applicants (fresh opportunities)
## `salary` (type: `string`):
Filter by minimum salary range
## `scrapeCompany` (type: `boolean`):
Fetch additional company page details (slower but more data)
## `scrapeJobDetails` (type: `boolean`):
Visit each job page for full description, criteria, and apply info
## `removeDuplicates` (type: `boolean`):
Cross-run deduplication via key-value store
## `splitByLocation` (type: `boolean`):
Split search by city to overcome 1000 result limit
## `splitCountry` (type: `string`):
Country code for location splitting (US, GB, CA, DE, etc.)
## `cookie` (type: `string`):
Optional. Your personal li\_at cookie for guaranteed results. The scraper works without it, but providing your own cookie ensures stability. Get it easily: https://chromewebstore.google.com/detail/linkedin-cookie-extractor/oojaeleepcoflmcknfbbbhhnkejdokmp
## `maxConcurrency` (type: `integer`):
Maximum parallel requests (keep low to avoid blocks)
## `maxRetries` (type: `integer`):
Maximum retries per failed request
## `requestDelay` (type: `integer`):
Minimum delay between requests in milliseconds
## `proxyConfiguration` (type: `object`):
Apify proxy configuration (residential fallback)
## Actor input object example
```json
{
"urls": [],
"keywords": "",
"location": "",
"geoId": "",
"count": 100,
"datePosted": "anytime",
"jobType": "any",
"experienceLevel": "any",
"workType": "any",
"sortBy": "relevance",
"easyApply": false,
"under10Applicants": false,
"salary": "any",
"scrapeCompany": false,
"scrapeJobDetails": true,
"removeDuplicates": true,
"splitByLocation": false,
"splitCountry": "US",
"maxConcurrency": 2,
"maxRetries": 3,
"requestDelay": 2000,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# Actor output Schema
## `id` (type: `string`):
LinkedIn job posting ID
## `title` (type: `string`):
Title of the job posting
## `companyName` (type: `string`):
Name of the hiring company
## `companyLinkedinUrl` (type: `string`):
LinkedIn page of the company
## `companyLogo` (type: `string`):
URL of the company logo image
## `location` (type: `string`):
Job location (city, country)
## `postedAt` (type: `string`):
Date the job was posted (ISO format)
## `postedAtTimestamp` (type: `string`):
Unix timestamp of posting date
## `salaryInfo` (type: `string`):
Salary range as shown on the listing
## `seniorityLevel` (type: `string`):
Experience level required
## `employmentType` (type: `string`):
Full-time, Part-time, Contract, etc.
## `jobFunction` (type: `string`):
Job category (Engineering, Marketing, etc.)
## `industries` (type: `string`):
Industry sectors of the company
## `applicantsCount` (type: `string`):
Number of applicants when shown by LinkedIn
## `applyMethod` (type: `string`):
LinkedIn Apply or External
## `descriptionText` (type: `string`):
Full job description in plain text
## `descriptionHtml` (type: `string`):
Full job description in HTML format
## `link` (type: `string`):
Direct link to the LinkedIn job posting
## `sourceUrl` (type: `string`):
Search URL that returned this job
## `scrapedAt` (type: `string`):
Timestamp when the job was scraped
# 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 = {};
// Run the Actor and wait for it to finish
const run = await client.actor("brilliant_gum/linkedin-jobs-premium-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 = {}
# Run the Actor and wait for it to finish
run = client.actor("brilliant_gum/linkedin-jobs-premium-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 '{}' |
apify call brilliant_gum/linkedin-jobs-premium-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=brilliant_gum/linkedin-jobs-premium-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Jobs Premium Scraper",
"description": "Scrape LinkedIn job listings at scale — no account required. Full descriptions, salary ranges, applicant counts, seniority levels and 20+ fields per job. Advanced filters: Easy Apply, salary minimum, under 10 applicants, remote/hybrid. Cross-run deduplication included.",
"version": "1.0",
"x-build-id": "NGfYzlpPtg9l8YKjj"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/brilliant_gum~linkedin-jobs-premium-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-brilliant_gum-linkedin-jobs-premium-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/brilliant_gum~linkedin-jobs-premium-scraper/runs": {
"post": {
"operationId": "runs-sync-brilliant_gum-linkedin-jobs-premium-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/brilliant_gum~linkedin-jobs-premium-scraper/run-sync": {
"post": {
"operationId": "run-sync-brilliant_gum-linkedin-jobs-premium-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"urls": {
"title": "Search URLs",
"type": "array",
"description": "LinkedIn job search URLs. If provided, overrides keywords/location params.",
"default": [],
"items": {
"type": "string"
}
},
"keywords": {
"title": "Search Keywords",
"type": "string",
"description": "Job search keywords (e.g., 'software engineer')",
"default": ""
},
"location": {
"title": "Location",
"type": "string",
"description": "Location filter (e.g., 'New York', 'London')",
"default": ""
},
"geoId": {
"title": "Geo ID",
"type": "string",
"description": "LinkedIn geographic ID for precise location filtering",
"default": ""
},
"count": {
"title": "Max Results",
"minimum": 10,
"maximum": 5000,
"type": "integer",
"description": "Maximum number of job results to scrape",
"default": 100
},
"datePosted": {
"title": "Date Posted",
"enum": [
"anytime",
"past24h",
"pastWeek",
"pastMonth"
],
"type": "string",
"description": "Filter by posting date",
"default": "anytime"
},
"jobType": {
"title": "Job Type",
"enum": [
"any",
"full-time",
"part-time",
"contract",
"temporary",
"volunteer",
"internship"
],
"type": "string",
"description": "Filter by employment type",
"default": "any"
},
"experienceLevel": {
"title": "Experience Level",
"enum": [
"any",
"internship",
"entry",
"associate",
"mid-senior",
"director",
"executive"
],
"type": "string",
"description": "Filter by experience level",
"default": "any"
},
"workType": {
"title": "Work Type",
"enum": [
"any",
"on-site",
"remote",
"hybrid"
],
"type": "string",
"description": "Filter by workplace type",
"default": "any"
},
"sortBy": {
"title": "Sort By",
"enum": [
"relevance",
"date"
],
"type": "string",
"description": "Sort results by relevance or date",
"default": "relevance"
},
"easyApply": {
"title": "Easy Apply Only",
"type": "boolean",
"description": "Only show jobs with LinkedIn Easy Apply",
"default": false
},
"under10Applicants": {
"title": "Under 10 Applicants",
"type": "boolean",
"description": "Only show jobs with fewer than 10 applicants (fresh opportunities)",
"default": false
},
"salary": {
"title": "Minimum Salary",
"enum": [
"any",
"40000",
"60000",
"80000",
"100000",
"120000",
"140000",
"160000",
"180000",
"200000"
],
"type": "string",
"description": "Filter by minimum salary range",
"default": "any"
},
"scrapeCompany": {
"title": "Scrape Company Details",
"type": "boolean",
"description": "Fetch additional company page details (slower but more data)",
"default": false
},
"scrapeJobDetails": {
"title": "Scrape Job Details",
"type": "boolean",
"description": "Visit each job page for full description, criteria, and apply info",
"default": true
},
"removeDuplicates": {
"title": "Remove Duplicates",
"type": "boolean",
"description": "Cross-run deduplication via key-value store",
"default": true
},
"splitByLocation": {
"title": "Split by Location",
"type": "boolean",
"description": "Split search by city to overcome 1000 result limit",
"default": false
},
"splitCountry": {
"title": "Split Country",
"type": "string",
"description": "Country code for location splitting (US, GB, CA, DE, etc.)",
"default": "US"
},
"cookie": {
"title": "LinkedIn Cookie (li_at) - Optional",
"type": "string",
"description": "Optional. Your personal li_at cookie for guaranteed results. The scraper works without it, but providing your own cookie ensures stability. Get it easily: https://chromewebstore.google.com/detail/linkedin-cookie-extractor/oojaeleepcoflmcknfbbbhhnkejdokmp"
},
"maxConcurrency": {
"title": "Max Concurrency",
"minimum": 1,
"maximum": 5,
"type": "integer",
"description": "Maximum parallel requests (keep low to avoid blocks)",
"default": 2
},
"maxRetries": {
"title": "Max Retries",
"minimum": 1,
"maximum": 10,
"type": "integer",
"description": "Maximum retries per failed request",
"default": 3
},
"requestDelay": {
"title": "Request Delay (ms)",
"minimum": 500,
"maximum": 10000,
"type": "integer",
"description": "Minimum delay between requests in milliseconds",
"default": 2000
},
"proxyConfiguration": {
"title": "Proxy Configuration",
"type": "object",
"description": "Apify proxy configuration (residential fallback)",
"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
}
}
}
}
}
}
}
}
}
}
```