# LinkedIn Jobs Scraper — Search & Filters (`globalapi/linkedin-jobs-scraper`) Actor

Search LinkedIn jobs by keyword and location without providing LinkedIn cookies. Filter by date, experience, job type, and applicants, then paginate structured job results.

- **URL**: https://apify.com/globalapi/linkedin-jobs-scraper.md
- **Developed by:** [GlobalAPI](https://apify.com/globalapi) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

**Find public LinkedIn job listings with role and hiring filters designed for repeatable market research.**

ToolzerHub maintains LinkedIn Pro Jobs Search Scraper for cross-company discovery. It combines keyword, location, company, experience, remote, job-type, Easy Apply, and applicant filters so each dataset represents a stated hiring question.

### Write the question before running the search

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| `keyword` | string | Yes | Search keyword, e.g. a title, skill, or topic. |
| `sort_by` | string | No | Sort results by the supported order, e.g. recent or relevant. |
| `date_posted` | string | No | Only return results posted within this window, e.g. past_24h, past_week, past_month. |
| `geocode` | string | No | A place name or geo ID to search jobs in. |
| `company` | string | No | A LinkedIn company handle, name, or /company/ URL. |
| `experience_level` | string | No | Only return jobs matching this experience level. |
| `remote` | boolean | No | Only return remote job listings. |
| `job_type` | string | No | Only return jobs matching this employment type, e.g. full_time, contract. |
| `easy_apply` | boolean | No | Only return jobs with LinkedIn Easy Apply enabled. |
| `has_verifications` | boolean | No | Only return jobs with verified employers. |
| `under_10_applicants` | boolean | No | Only return jobs with fewer than 10 applicants. |
| `fair_chance_employer` | boolean | No | Only return jobs from fair chance employers. |
| `maxItems` | integer | No | Maximum number of results to save. Set 0 for unlimited. |

#### Example role scan

```json
{
  "keyword": "Software Engineer",
  "maxItems": 20
}
```

### Treat search rows as an index

| Field | Type | Description |
| --- | --- | --- |
| `id` | string | Record ID. |
| `title` | string | Title of the record (job title, etc). |
| `company` | string | Company name or handle associated with the record. |
| `url` | string | Canonical LinkedIn URL for the record. |
| `page` | number | Page number this record was returned on, for paginated endpoints. |
| `data` | object | Additional fields that are not explicitly modeled above. |

#### Listing preview

```json
{
  "id": "4318514364",
  "title": "Software Engineer",
  "company": "Voltai"
}
```

Run the same saved input on a schedule to compare changes, and deduplicate stable job IDs before calculating openings or growth.

### Cost of repeated market scans

This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab.

Apify's free credits may cover small test runs and up to the free result allowance configured for the Actor.

Start with a low maxItems value before scaling up a run.

### Job-data responsibility

This Actor extracts publicly available LinkedIn data. It should not be used to collect private data, bypass access controls, or contact people in ways that violate privacy laws, LinkedIn terms, or your own compliance obligations. Personal data may be protected by GDPR and similar laws. If you are unsure, consult a qualified lawyer.

### Run this Actor from code

#### Python

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")
run = client.actor("toolzerhub/linkedin-jobs-scraper").call(run_input={
    "keyword": "Software Engineer",
    "maxItems": 20
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

#### Node.js

```javascript
import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" });
const run = await client.actor("toolzerhub/linkedin-jobs-scraper").call({
  "keyword": "Software Engineer",
  "maxItems": 20
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

### Resolve jobs or focus on one employer

- [LinkedIn Job Details Scraper — No Cookies](https://apify.com/toolzerhub/linkedin-job-details-scraper) — Fetch complete public LinkedIn job postings for one or more job IDs without providing LinkedIn cookies. Optionally include skills and export structured job details in one run.
- [LinkedIn Company Jobs Scraper — No Cookies](https://apify.com/toolzerhub/linkedin-company-jobs-scraper) — Collect open jobs from a LinkedIn company page without providing LinkedIn cookies. Filter by date, experience, job type, and applicants, then paginate and export structured listings.
- [LinkedIn Company Scraper — No Cookies](https://apify.com/toolzerhub/linkedin-company-scraper) — Extract complete public LinkedIn company pages from company handles or IDs without providing LinkedIn cookies. Batch company inputs and receive structured company details for every result.

### ToolzerHub support

Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests.

# Actor input Schema

## `keyword` (type: `string`):

Search keyword, e.g. a title, skill, or topic.

## `sort_by` (type: `string`):

Sort results by the supported order, e.g. recent or relevant.

## `date_posted` (type: `string`):

Only return results posted within this window, e.g. past_24h, past_week, past_month.

## `geocode` (type: `string`):

A place name or geo ID to search jobs in.

## `company` (type: `string`):

A LinkedIn company handle, name, or /company/ URL.

## `experience_level` (type: `string`):

Only return jobs matching this experience level.

## `remote` (type: `boolean`):

Only return remote job listings.

## `job_type` (type: `string`):

Only return jobs matching this employment type, e.g. full_time, contract.

## `easy_apply` (type: `boolean`):

Only return jobs with LinkedIn Easy Apply enabled.

## `has_verifications` (type: `boolean`):

Only return jobs with verified employers.

## `under_10_applicants` (type: `boolean`):

Only return jobs with fewer than 10 applicants.

## `fair_chance_employer` (type: `boolean`):

Only return jobs from fair chance employers.

## `maxItems` (type: `integer`):

Maximum number of results to save. Set 0 for unlimited.

## Actor input object example

```json
{
  "keyword": "Artificial Intelligence",
  "company": "apple",
  "remote": false,
  "easy_apply": false,
  "has_verifications": false,
  "under_10_applicants": false,
  "fair_chance_employer": false,
  "maxItems": 20
}
```

# Actor output Schema

## `dataset` (type: `string`):

Dataset containing all scraped data

# 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 = {
    "keyword": "Artificial Intelligence",
    "company": "apple",
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("globalapi/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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keyword": "Artificial Intelligence",
    "company": "apple",
    "maxItems": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("globalapi/linkedin-jobs-scraper").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 '{
  "keyword": "Artificial Intelligence",
  "company": "apple",
  "maxItems": 20
}' |
apify call globalapi/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

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

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/29X6Pwr7lnDPp1ZRR/builds/Q9jzzAfhRPXrJPEJ4/openapi.json