# Linkedin Jobs Scraper - $0.1 per 1k (`supreme_coder/linkedin-jobs-scraper`) Actor
Cheapest Linkedin jobs scraper. 99% success rate. Actively maintained
- **URL**: https://apify.com/supreme\_coder/linkedin-jobs-scraper.md
- **Developed by:** [Supreme Coder](https://apify.com/supreme_coder) (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 $0.25 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
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
Extract structured job listings from LinkedIn search results — no LinkedIn account or session cookies required. Paste a public jobs search URL and get full posting details, recruiter info, and optional company profiles in a ready-to-use dataset.
### Why use this scraper?
Most LinkedIn scrapers depend on authenticated sessions, which means managing cookies, handling expired logins, and risking account restrictions. This actor works against LinkedIn's **public** jobs pages instead. You build your search in a private/incognito browser window, copy the URL, and the actor handles the rest.
**Best for:** job market research, lead generation, competitive hiring analysis, recruiting pipelines, and scheduled monitoring of new postings.
### Quick start
1. Open an **incognito/private** browser window and go to [LinkedIn Jobs Search](https://www.linkedin.com/jobs/search/).
2. Apply your filters (keywords, location, experience level, date posted, etc.).
3. Copy the **full URL** from the address bar.
4. Paste it into the **Linkedin jobs search URLs** input field.
5. Set how many jobs you need and run the actor.
> **Important:** URLs created while logged into LinkedIn may include filters that only work for authenticated users. Always build your search URL in incognito mode so results match what this actor can access.
### Input options
| Input | Description |
|-------|-------------|
| **Linkedin jobs search URLs** | One or more public job search URLs. Pass multiple URLs to scrape several searches in a single run. |
| **Number of jobs needed** | Maximum records to collect (minimum 10). |
| **Scrape company details** | Fetches the employer's LinkedIn company page for each job. Adds extra requests and increases run time. |
| **Split search by city locations** | Breaks a broad search into city-level queries to work around LinkedIn's per-search cap. Requires at least 1,100 jobs. |
| **Country to split by** | Target country whose cities are used when location splitting is enabled. Replaces the location filter in your input URLs. |
**Memory tip:** Allocate at least **1 GB of actor memory per search URL** you provide. For example, 4 URLs need 4 GB RAM.
### Search URL parameters
Filters are read directly from your search URL query string. Any filter you set on the LinkedIn jobs page is preserved automatically.
| Parameter | What it filters |
|-----------|-----------------|
| `keywords` | Job title or keyword search |
| `geoId` | Geographic location ID |
| `location` | Location display name |
| `sortBy` | Result ordering (e.g. `R` for most recent) |
| `f_C` | Specific company |
| `f_E` | Experience level |
| `f_F` | Job function / department |
| `f_I` | Industry |
| `f_JT` | Job type (full-time, contract, etc.) |
| `f_T` | Job title |
| `f_TPR` | Custom date posted range |
| `f_TP` | Time posted (e.g. past 24 hours) |
| `f_WT` | Workplace type (on-site, remote, hybrid) |
| `f_WRA` | Remote work allowed |
| `f_SB2` | Salary range |
| `f_PP` | Populated place |
| `f_CM` | Company commitments |
| `f_AL` | Easy Apply |
| `f_EA` | Under 10 applicants |
| `f_JIYN` | Jobs at companies in your network |
| `f_VJ` | Verified jobs |
### Output fields
Each dataset record represents one job posting. Fields are populated when LinkedIn exposes them on the public page.
**Job listing**
- `id`, `link`, `title`, `location`, `postedAt`, `postedAtTimestamp`
- `salaryInfo`, `benefits`, `insights`
- `descriptionHtml`, `descriptionText`
- `applicantsCount`, `applyUrl`, `applyMethod`
- `seniorityLevel`, `employmentType`, `jobFunction`, `industries`
- `workRemoteAllowed`, `workplaceTypes`, `expireAt`
- `salaryInsights`
**Recruiter / poster**
- `jobPosterName`, `jobPosterTitle`, `jobPosterPhoto`, `jobPosterProfileUrl`
**Company** (when **Scrape company details** is enabled)
- `companyName`, `companyLinkedinUrl`, `companyLogo`
- `companyDescription`, `companyWebsite`, `companyEmployeesCount`
**Run metadata**
- `inputUrl` — the search URL that surfaced this job
### Example output
```json
{
"id": "4123456789",
"link": "https://www.linkedin.com/jobs/view/senior-product-manager-at-stripe-4123456789",
"title": "Senior Product Manager",
"companyName": "Stripe",
"companyLinkedinUrl": "https://www.linkedin.com/company/stripe",
"companyLogo": "https://media.licdn.com/dms/image/example/company-logo_100_100/0",
"location": "San Francisco, CA",
"salaryInfo": ["$180,000", "$220,000"],
"postedAt": "2025-06-12",
"benefits": ["Actively Hiring"],
"descriptionHtml": "We're looking for a Senior Product Manager to lead...
",
"descriptionText": "We're looking for a Senior Product Manager to lead...",
"applicantsCount": "47",
"jobPosterName": "Sarah Chen",
"jobPosterTitle": "Talent Partner at Stripe",
"seniorityLevel": "Mid-Senior level",
"employmentType": "Full-time",
"jobFunction": "Product Management",
"industries": "Financial Services, Technology",
"companyDescription": "Stripe is a financial infrastructure platform for businesses.",
"companyWebsite": "https://stripe.com",
"companyEmployeesCount": 8000,
"workRemoteAllowed": true,
"workplaceTypes": ["Hybrid", "Remote"]
}
````
Export results as JSON, CSV, Excel, or any format Apify datasets support.
### Scraping more than 1,000 jobs
LinkedIn caps each search at roughly 1,000 results, even when more jobs match your criteria. To go further:
1. Enable **Split search by city locations**.
2. Choose a **Country to split by**.
3. Set **Number of jobs needed** to at least **1,100**.
The actor generates separate search URLs for cities within that country, reusing your other filters. Duplicate listings are skipped automatically.
### Daily new-job monitoring
To track fresh postings on a schedule:
1. In an incognito window, set the date filter to **Past 24 hours** (or your preferred window).
2. Configure your other filters and copy the search URL.
3. Schedule this actor to run daily with that URL.
The relative date filter stays valid across runs — you do not need to generate a new URL each day.
### API access
Results are stored in an Apify dataset. Pull data programmatically via the Apify API or export on demand from the run's **Storage** tab. Use dataset endpoints to integrate with your CRM, spreadsheet, or data warehouse.
### Related tools
- [Contact Info Finder](https://apify.com/supreme_coder/contact-info-finder) — verified emails and contact details for companies you discover through job scraping.
### Integrations
Connect this actor to other platforms with [Make](https://www.make.com/en/register?pc=growthhack) or any workflow tool that supports Apify webhooks and dataset APIs.
# Actor input Schema
## `urls` (type: `array`):
Go to [linkedin jobs search page](https://www.linkedin.com/jobs/search/) on incognito window (to access public version), search with required filters and once you are done, copy the full URL from address bar and pass it here. You can pass multiple search URLs
## `scrapeCompany` (type: `boolean`):
This will require additional scraping requests for each job record and take longer to scrape
## `count` (type: `integer`):
Limit number of jobs scraped
## `splitByLocation` (type: `boolean`):
Enable this to split your search by cities within a country. This helps bypass LinkedIn's 1000 job limit per search URL by creating separate searches for each city. This will overwrite the location filter in input search URLs.
## `splitCountry` (type: `string`):
Select the country whose cities will be used to split the search. Only used when 'Split search by city locations' is enabled. Required to when 'Split search by city locations' is enabled.
## Actor input object example
```json
{
"urls": [
"https://www.linkedin.com/jobs/search/?position=1&pageNum=0"
],
"scrapeCompany": true,
"count": 100,
"splitByLocation": false
}
```
# 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 = {
"urls": [
"https://www.linkedin.com/jobs/search/?position=1&pageNum=0"
],
"count": 100
};
// Run the Actor and wait for it to finish
const run = await client.actor("supreme_coder/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 = {
"urls": ["https://www.linkedin.com/jobs/search/?position=1&pageNum=0"],
"count": 100,
}
# Run the Actor and wait for it to finish
run = client.actor("supreme_coder/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 '{
"urls": [
"https://www.linkedin.com/jobs/search/?position=1&pageNum=0"
],
"count": 100
}' |
apify call supreme_coder/linkedin-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=supreme_coder/linkedin-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Linkedin Jobs Scraper - $0.1 per 1k",
"description": "Cheapest Linkedin jobs scraper. 99% success rate. Actively maintained",
"version": "1.5",
"x-build-id": "fXgRI00vplgRrr4ZA"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/supreme_coder~linkedin-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-supreme_coder-linkedin-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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/supreme_coder~linkedin-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-supreme_coder-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/supreme_coder~linkedin-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-supreme_coder-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": [
"urls"
],
"properties": {
"urls": {
"title": "Linkedin jobs search URLs",
"type": "array",
"description": "Go to [linkedin jobs search page](https://www.linkedin.com/jobs/search/) on incognito window (to access public version), search with required filters and once you are done, copy the full URL from address bar and pass it here. You can pass multiple search URLs",
"items": {
"type": "string"
}
},
"scrapeCompany": {
"title": "Scrape company details",
"type": "boolean",
"description": "This will require additional scraping requests for each job record and take longer to scrape",
"default": true
},
"count": {
"title": "Number of jobs needed",
"minimum": 10,
"type": "integer",
"description": "Limit number of jobs scraped"
},
"splitByLocation": {
"title": "Split search by city locations",
"type": "boolean",
"description": "Enable this to split your search by cities within a country. This helps bypass LinkedIn's 1000 job limit per search URL by creating separate searches for each city. This will overwrite the location filter in input search URLs.",
"default": false
},
"splitCountry": {
"title": "Country to split by",
"enum": [
"US",
"CA",
"MX",
"GB",
"DE",
"FR",
"NL",
"CH",
"SE",
"NO",
"DK",
"FI",
"IE",
"ES",
"IT",
"PT",
"BE",
"AT",
"PL",
"CZ",
"RO",
"HU",
"GR",
"BG",
"HR",
"RS",
"UA",
"SK",
"LT",
"LV",
"EE",
"SI",
"LU",
"MT",
"IS",
"CY",
"TR",
"RU",
"GE",
"AM",
"AZ",
"BY",
"BA",
"XK",
"MD",
"ME",
"MK",
"AL",
"MC",
"AD",
"LI",
"SM",
"VA",
"IN",
"CN",
"JP",
"KR",
"SG",
"HK",
"TW",
"TH",
"VN",
"ID",
"MY",
"PH",
"BD",
"PK",
"LK",
"NP",
"MM",
"KH",
"KZ",
"UZ",
"KG",
"TJ",
"TM",
"MN",
"BN",
"MV",
"BT",
"LA",
"TL",
"AF",
"KP",
"AE",
"SA",
"IL",
"QA",
"KW",
"BH",
"OM",
"JO",
"LB",
"IQ",
"IR",
"PS",
"SY",
"YE",
"AU",
"NZ",
"FJ",
"PG",
"WS",
"TO",
"VU",
"SB",
"KI",
"MH",
"FM",
"PW",
"NR",
"TV",
"BR",
"AR",
"CO",
"CL",
"PE",
"EC",
"UY",
"VE",
"BO",
"PY",
"GY",
"SR",
"CR",
"PA",
"GT",
"DO",
"PR",
"JM",
"TT",
"HN",
"SV",
"NI",
"BS",
"BB",
"CU",
"HT",
"BZ",
"AG",
"DM",
"GD",
"LC",
"KN",
"VC",
"ZA",
"NG",
"KE",
"EG",
"MA",
"GH",
"ET",
"TZ",
"RW",
"UG",
"SN",
"TN",
"CI",
"CM",
"DZ",
"AO",
"MU",
"ZM",
"ZW",
"MZ",
"CD",
"BW",
"NA",
"MG",
"LY",
"SD",
"SS",
"SO",
"ML",
"GA",
"BJ",
"BF",
"MW",
"NE",
"TD",
"SL",
"LR",
"ER",
"GM",
"GN",
"GW",
"TG",
"MR",
"SZ",
"LS",
"DJ",
"CG",
"CF",
"BI",
"CV",
"KM",
"GQ",
"ST",
"SC"
],
"type": "string",
"description": "Select the country whose cities will be used to split the search. Only used when 'Split search by city locations' is enabled. Required to when 'Split search by city locations' is enabled."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```