# LinkedIn Jobs Scraper - No Login, Full Descriptions (`solarg/linkedin-jobs-scraper`) Actor

Scrape LinkedIn job listings by keyword and location with full descriptions, salary, seniority, employment type, industries, applicant count and apply type. Filters for date posted, distance, job type and experience level. No login or cookies.

- **URL**: https://apify.com/solarg/linkedin-jobs-scraper.md
- **Developed by:** [Solar G](https://apify.com/solarg) (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 $0.35 / 1,000 job listeds

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

Scrapes LinkedIn job listings by keyword and location from LinkedIn's public job search, with no login or cookies. With details turned on, each job also has its full description (plain text and HTML), salary (when listed), seniority level, employment type, industries, applicant count, apply type and the employer's LinkedIn company ID.

### Input

| Field | Description |
|---|---|
| `searches` | Job keywords, e.g. `"data engineer"`, `"nurse"`. |
| `location` | City, region or country. Leave empty for worldwide. |
| `distance` | Optional radius around the location in miles: `0`, `5`, `10`, `25`, `50` or `100`. |
| `maxJobsPerSearch` | Default 100. LinkedIn shows up to about 1,000 jobs per search. |
| `postedWithin` | `any`, `day`, `week` or `month`. |
| `jobTypes` | Keep only `fulltime`, `parttime`, `contract`, `temporary`, `internship`, `volunteer` or `other` jobs. |
| `experienceLevels` | Keep only `internship`, `entry`, `associate`, `midsenior`, `director`, `executive` or `notapplicable` jobs. |
| `includeDetails` | Full description and job criteria. Default `true`. |

```json
{
  "searches": ["data engineer", "analytics engineer"],
  "location": "London",
  "distance": "10",
  "postedWithin": "week",
  "experienceLevels": ["entry", "associate"],
  "maxJobsPerSearch": 200
}
```

How the inputs work:

- **Location** is matched to a LinkedIn location first. If LinkedIn does not recognise it, the run returns an error item for each search instead of worldwide results. Add a country to avoid ambiguous names, e.g. `"Cambridge, England"`.
- **Date posted** and **distance** are applied by LinkedIn.
- **Job type** and **experience level** are not applied by LinkedIn's logged-out search, so the Actor reads each job's details and keeps only the jobs that match. This takes longer (many jobs may be read for each match), so each search checks at most 6 listings per job requested (at least 60) for up to about 75 seconds. A rare combination may therefore return fewer jobs than requested. If `includeDetails` is off, the details are used only for filtering and are not charged.
- Remote, hybrid and on-site filters and "sort by date" are not offered: LinkedIn's logged-out search ignores them. `workplaceType` is filled in only when the job title or location says "remote", "hybrid" or "on-site".

### Output

```json
{
  "search": "data engineer",
  "searchLocation": "London",
  "jobId": "4480480883",
  "title": "Data Engineer",
  "company": "LA International",
  "companyId": "27624",
  "companyUrl": "https://uk.linkedin.com/company/la-international",
  "location": "London Area, United Kingdom",
  "workplaceType": null,
  "postedDate": "2026-10-20",
  "postedText": "3 days ago",
  "salary": "£55,000.00/yr - £75,000.00/yr",
  "benefits": "Actively Hiring",
  "url": "https://www.linkedin.com/jobs/view/4480480883",
  "companyLogo": "https://media.licdn.com/dms/image/...",
  "description": "Data Engineer | SC Cleared / SC Eligible\nHybrid working in London\n...",
  "descriptionHtml": "<p><strong>Data Engineer | SC Cleared / SC Eligible</strong></p>...",
  "seniorityLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "industries": "IT Services and IT Consulting, Financial Services, and Defense and Space Manufacturing",
  "applicants": "98 applicants",
  "applicantsCount": 98,
  "applicantsCountIsMinimum": false,
  "applyType": "linkedin"
}
```

- `applicantsCount` is the number LinkedIn shows. For "Over 200 applicants" it is `200` with `applicantsCountIsMinimum: true`. For "Be among the first 25 applicants" it is `null`.
- `applyType` is `linkedin` (apply on LinkedIn) or `external` (apply on the employer's site).
- Jobs that appear in more than one search are returned once.
- If a job's details cannot be read (expired, removed, or LinkedIn did not answer), the job has a `detailsError` and is not charged the details add-on.
- A search that finds nothing, or a location LinkedIn does not recognise, returns an error item: `{ "type": "error", "search": "...", "input": "...", "searchLocation": "...", "error": "..." }`. Error items are free.

### API usage

```bash
curl -X POST "https://api.apify.com/v2/acts/solarg~linkedin-jobs-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searches": ["data engineer"], "location": "London", "postedWithin": "day"}'
```

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("solarg/linkedin-jobs-scraper").call(run_input={"searches": ["nurse"], "location": "Manchester"})
items = client.dataset(run["defaultDatasetId"]).list_items().items
```

Schedule a daily run with `postedWithin: "day"` to get a feed of new jobs.

### Pricing

- $0.50 per 1,000 jobs (listing)
- $0.50 per 1,000 jobs for full details (only when `includeDetails` is on, and only for jobs whose details were read)

Error items are free. Platform usage is included in the price.

### Limitations

- Only public job postings are available. No profiles, recruiter names or applicant data.
- Salary appears only when the employer publishes it.
- LinkedIn limits each search to about 1,000 results. Use narrower searches for more.
- When a run is close to its timeout, the Actor stops early and saves what it has, so the run still succeeds.

Report problems in the Issues tab.

# Actor input Schema

## `searches` (type: `array`):

Keywords to search, e.g. "data engineer", "nurse", "product manager".

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

City, region or country, e.g. London, Texas, United States. It is matched to a LinkedIn location; an unrecognised location returns an error item instead of worldwide results. Leave empty for worldwide.

## `distance` (type: `string`):

Search radius around the location, in miles. Leave empty for LinkedIn's default (about 25 miles for a city).

## `maxJobsPerSearch` (type: `integer`):

LinkedIn shows up to about 1,000 jobs per search.

## `postedWithin` (type: `string`):

Only jobs posted within this period.

## `jobTypes` (type: `array`):

Keep only jobs with these employment types, checked against each job's details. Leave empty for all.

## `experienceLevels` (type: `array`):

Keep only jobs with these seniority levels, checked against each job's details. Leave empty for all.

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

Full description (text and HTML), seniority, employment type, industries, applicant count, apply type and LinkedIn company ID. Charged as an add-on per job, only when the details were read.

## Actor input object example

```json
{
  "searches": [
    "data engineer"
  ],
  "location": "London",
  "maxJobsPerSearch": 25,
  "postedWithin": "any",
  "includeDetails": true
}
```

# Actor output Schema

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

Job records in table form (the Jobs view of the dataset).

## `results` (type: `string`):

Every item in the default dataset, including error items.

# 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 = {
    "searches": [
        "data engineer"
    ],
    "location": "London",
    "maxJobsPerSearch": 25
};

// Run the Actor and wait for it to finish
const run = await client.actor("solarg/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 = {
    "searches": ["data engineer"],
    "location": "London",
    "maxJobsPerSearch": 25,
}

# Run the Actor and wait for it to finish
run = client.actor("solarg/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 '{
  "searches": [
    "data engineer"
  ],
  "location": "London",
  "maxJobsPerSearch": 25
}' |
apify call solarg/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,solarg/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/zhdWBREf6XKCrQVkr/builds/XHgddigoWDNEGlwiE/openapi.json