# LinkedIn Jobs Search Scraper - Half Price (`unbrowseai/linkedin-jobs-search`) Actor

Scrape LinkedIn job postings by keyword, location or search URL: title, company, location, salary, date, applicants, full description, seniority, employment type, industries. No login, no cookies.

- **URL**: https://apify.com/unbrowseai/linkedin-jobs-search.md
- **Developed by:** [Unbrowse AI](https://apify.com/unbrowseai) (community)
- **Categories:** Jobs, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 jobs

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Jobs Search Scraper

Pull job postings from LinkedIn's public job search into a clean table: title, company, location, salary (when posted), date, applicant count and the full job description with seniority, employment type, job function and industries. No LinkedIn account, cookies or proxies needed on your side.

### What you can do with it

- **Recruiting and sourcing** – track who is hiring for a role in a city, every day.
- **Job boards and aggregators** – feed fresh postings into your own site or newsletter.
- **Market research** – measure hiring demand by skill, seniority or industry over time.
- **Lead generation** – companies that are hiring are companies that are buying.

### How to use it

1. Type **keywords** (e.g. `data engineer`) and a **location** (e.g. `London`), or paste one or more LinkedIn job search URLs with the filters you already set on linkedin.com.
2. Optionally narrow by date posted, job type, experience level and workplace type (on-site, remote, hybrid).
3. Set **Max jobs** and press Start. Results appear in the dataset as they are found; export them as JSON, CSV, Excel or via the API.

LinkedIn shows at most about 1,000 results for a single search. For more, split the search by location or filters.

### Output example

```json
{
  "id": "4467786531",
  "title": "Senior Data Engineer",
  "companyName": "Firstup",
  "companyUrl": "https://www.linkedin.com/company/firstup-io",
  "location": "London, England, United Kingdom",
  "salary": null,
  "salaryRange": { "raw": "$120,000 - $200,000", "min": 120000, "max": 200000, "period": "year", "currency": "USD" },
  "postedAt": "2026-09-15",
  "postedTimeAgo": "1 week ago",
  "applicantsCount": "Be among the first 25 applicants",
  "seniorityLevel": "Not Applicable",
  "employmentType": "Full-time",
  "jobFunction": "Information Technology",
  "industries": "Software Development",
  "descriptionText": "Who We Are\nAt Firstup, our mission is ...",
  "url": "https://uk.linkedin.com/jobs/view/senior-data-engineer-at-firstup-4467786531",
  "scrapedAt": "2026-09-27T16:20:33.563Z"
}
```

### Pricing

You pay per job returned, and the full details (description, seniority, industries, applicants) are included at no extra cost:

| Apify plan | Price per 1,000 jobs |
|---|---|
| Free | $1.00 |
| Starter and above | $0.50 |

That is roughly half of what comparable LinkedIn job scrapers charge. A small fee applies to each run start, as on every pay-per-event Actor. Set a maximum cost per run in the run options and the scraper stops cleanly when it is reached.

### FAQ

**Do I need a LinkedIn account?** No. Only publicly visible job postings are collected.

**Why are some salaries empty?** `salary` is LinkedIn's own salary badge, which few postings have. `salaryRange` is also read from the job description (e.g. "Base pay: $120,000 - $200,000"), with min, max, period and currency, so you get pay data for far more jobs. It is null when the posting states no pay.

**Can I schedule it?** Yes. Use Apify schedules to run it daily and integrations (webhooks, Google Sheets, Zapier, Make) to send new jobs anywhere.

**Is it legal?** This Actor only collects publicly available job listings. You are responsible for how you use the data, including compliance with data protection law in your jurisdiction and the website's terms.

Found a problem or need a field that is missing? Open an issue on the Issues tab and it will be looked at quickly.

# Actor input Schema

## `keywords` (type: `string`):

Job title, skill or company, as you would type it in LinkedIn's job search box.

## `location` (type: `string`):

City, region or country, e.g. 'London' or 'United States'.

## `searchUrls` (type: `array`):

Optional. Paste job search URLs from linkedin.com/jobs/search with any filters applied. Used in addition to keywords/location.

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

Only jobs posted within this window.

## `jobType` (type: `array`):

Filter by one or more job types.

## `experienceLevel` (type: `array`):

Filter by one or more experience levels.

## `workplaceType` (type: `array`):

Filter by on-site, remote or hybrid.

## `maxJobs` (type: `integer`):

Stop after this many jobs in total. LinkedIn shows at most about 1,000 per search.

## `includeDetails` (type: `boolean`):

Open each job to add the full description, seniority, employment type, job function, industries and applicant count. Same price either way.

## Actor input object example

```json
{
  "keywords": "data engineer",
  "location": "London",
  "searchUrls": [],
  "datePosted": "any",
  "jobType": [],
  "experienceLevel": [],
  "workplaceType": [],
  "maxJobs": 10,
  "includeDetails": true
}
```

# Actor output Schema

## `jobs` (type: `string`):

No description

# 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": "data engineer",
    "location": "London",
    "maxJobs": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("unbrowseai/linkedin-jobs-search").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": "data engineer",
    "location": "London",
    "maxJobs": 10,
}

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

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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": "data engineer",
  "location": "London",
  "maxJobs": 10
}' |
apify call unbrowseai/linkedin-jobs-search --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,unbrowseai/linkedin-jobs-search"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/KouvzlLll7L2wZeIz/builds/6QZ0rKoGxUsVHKAFd/openapi.json