# LinkedIn Jobs Scraper — No Login, Full Job Details (`datakiln/linkedin-jobs-scraper`) Actor

Scrape LinkedIn job listings by keyword, location or search URL without login or cookies: title, company, location, date, full description, seniority, employment type, applicants, Easy Apply and salary.

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

## Pricing

$1.00 / 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.

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 Scraper — no login, full job details

Extract job listings from **LinkedIn Jobs** without a LinkedIn account, cookies or browser extension. Type a keyword and a location (or paste a LinkedIn job search URL) and get clean, structured data for each job: title, company, location, posting date, **full description**, seniority level, employment type, industries, applicant count, Easy Apply flag and salary when LinkedIn shows one.

**Pay only for what you get: $1 per 1,000 jobs, full details included.** No monthly rental, no start fees.

### What can you do with it?

- 🧑‍💼 **Job boards and aggregators.** Feed fresh LinkedIn postings into your own site or newsletter. Use *Sort by: Most recent* and *Date posted: Past 24 hours* on a daily schedule.
- 📊 **Labour-market research.** See who is hiring, for which roles, at what seniority and in which cities, and track it over time.
- 🎯 **Sales and recruiting leads.** Companies hiring for a role are often buying the tools around it. Get company names and LinkedIn company pages for every opening.
- 🤖 **AI and matching pipelines.** Full description text and HTML, ready for embeddings, classification or CV matching.
- 🔔 **Job alerts.** Monitor remote, hybrid or Easy Apply jobs for a set of keywords.

### How to use

1. Enter one or more **search keywords** (`python developer`, `data analyst`) and a **location** (`United States`, `London`, `Berlin, Germany`). You can also paste LinkedIn job search URLs straight from your browser instead.
2. Optionally filter by date posted, experience level, job type, on-site/remote/hybrid and Easy Apply, and set *Max jobs per search*.
3. Click **Start**, then download the results as JSON, CSV, Excel or HTML, or send them to Make, Zapier, n8n, Google Sheets or your own API.

### Input example

```json
{
  "searchQueries": ["data analyst", "marketing manager"],
  "location": "London",
  "datePosted": "pastWeek",
  "workplaceType": ["remote", "hybrid"],
  "experienceLevel": ["entry", "associate"],
  "maxJobsPerQuery": 200,
  "fetchJobDetails": true
}
```

Or reuse a search you set up on LinkedIn:

```json
{
  "searchUrls": ["https://www.linkedin.com/jobs/search/?keywords=react%20developer&location=Germany&f_TPR=r604800&f_WT=2"],
  "maxJobsPerQuery": 100
}
```

### Output example

```json
{
  "jobId": "4460718818",
  "jobUrl": "https://www.linkedin.com/jobs/view/senior-devops-engineer-at-logicalis-germany-4460718818",
  "title": "Senior DevOps Engineer",
  "companyName": "Logicalis Germany",
  "companyUrl": "https://www.linkedin.com/company/logicalisde",
  "companyLogoUrl": "https://media.licdn.com/dms/image/v2/…/company-logo_100_100/…",
  "location": "Frankfurt am Main, Hesse, Germany",
  "postedAt": "2026-09-24",
  "postedText": "2 weeks ago",
  "salary": null,
  "isEasyApply": false,
  "isClosed": false,
  "applicantsText": "56 applicants",
  "seniorityLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "jobFunction": null,
  "industries": "IT Services and IT Consulting",
  "insight": "Actively Hiring",
  "applyUrl": null,
  "description": "As a Senior DevOps Engineer you will …",
  "descriptionHtml": "<strong>Your role</strong><br><ul><li>…</li></ul>",
  "searchQuery": "devops engineer",
  "searchUrl": "https://www.linkedin.com/jobs/search/?keywords=devops+engineer&location=Germany",
  "scrapedAt": "2026-10-09T15:35:17+00:00"
}
```

#### All fields

| Field | Description |
|---|---|
| `jobId`, `jobUrl` | LinkedIn job ID and a direct link to the posting |
| `title` | Job title |
| `companyName`, `companyUrl`, `companyLogoUrl` | Hiring company, its LinkedIn page and logo |
| `location` | Job location as shown on LinkedIn |
| `postedAt`, `postedText` | Posting date (ISO `YYYY-MM-DD`) and LinkedIn's relative text ("3 days ago") |
| `salary` | Salary range, when LinkedIn shows one on the listing |
| `isEasyApply` | `true` = apply with LinkedIn Easy Apply, `false` = apply on the company's website |
| `isClosed` | `true` when the posting says "No longer accepting applications" |
| `applicantsText` | "Be among the first 25 applicants", "68 applicants", "Over 200 applicants" |
| `seniorityLevel`, `employmentType` | e.g. "Mid-Senior level", "Full-time" |
| `industries`, `jobFunction` | Company industry and job function, when LinkedIn shows them |
| `insight` | LinkedIn's highlight on the card, e.g. "Actively Hiring", "Be an early applicant" |
| `applyUrl` | External apply link, when LinkedIn exposes it publicly |
| `description`, `descriptionHtml` | Full job description as clean text (line breaks, bullets) and the original HTML |
| `searchQuery`, `searchUrl` | Which of your searches found the job, and the equivalent LinkedIn search URL |
| `scrapedAt` | When the job was scraped (UTC) |

With *Get full job details* turned off you get only the card fields (title, company, location, dates and Easy Apply when filtered). It's faster and costs the same.

### Filters

| Input | LinkedIn filter |
|---|---|
| *Date posted*: any / past 24 hours / past week / past month | `f_TPR` |
| *Experience level*: internship, entry, associate, mid-senior, director, executive | `f_E` |
| *Job type*: full-time, part-time, contract, temporary, internship, volunteer, other | `f_JT` |
| *On-site / remote*: on-site, remote, hybrid | `f_WT` |
| *Easy Apply only* | `f_AL` |
| *Sort by*: most relevant / most recent | `sortBy` |

For **search URLs**, every filter already in the URL (including `geoId`, `distance`, `f_C` company filters and so on) is kept as it is. The input filters only add what the URL doesn't set.

### Pricing

Pay per result: **$0.001 per job** ($1 per 1,000 jobs), with full details included. Platform usage is included. You can cap what a run costs with *Max total charge* in the run options. The scraper stops cleanly when it reaches the cap.

Each job is saved and charged **once per run**, even when several of your searches return it.

### FAQ

**Do I need a LinkedIn account or cookies?** No. The scraper uses only LinkedIn's **public job listings**, the same pages anyone can open in a private browser window without logging in. No login, cookies or accounts are used, so your own LinkedIn account is never at risk.

**Why do I get at most ~1,000 jobs per search?** LinkedIn's public job search stops after about 1,000 results for any single search, however many jobs it says it has. To collect more, **split the search**: run the same keywords in several locations (cities instead of a country), use narrower date windows (*past 24 hours* on a daily schedule), or split by experience level, job type or remote/hybrid. Each search gets its own 1,000-result window, and duplicates across searches are removed automatically.

**Why are some fields empty?** LinkedIn shows salary, applicant count, job function and the external apply link only for some postings, and often not to logged-out visitors. When a value isn't public, the field is `null`. You still get the job and its description.

**A job's details are missing. Why?** If a posting is closed or removed between the search and the detail request, or LinkedIn rate-limits a request after several retries on new IPs, you still get the card data (title, company, location, date), and the run continues.

**How fast is it?** About 200 jobs with full details per minute with the default settings. Card-only scrapes (*Get full job details* off) are several times faster.

**Can I monitor new jobs?** Yes. Schedule the Actor with *Sort by: Most recent* and *Date posted: Past 24 hours*, and connect the dataset to your sheet, Slack or database.

**Is it legal?** The scraper collects only publicly available job postings that companies publish so people will see them. You are responsible for using the data in line with LinkedIn's terms and the laws that apply to you, including data-protection rules for any personal data.

### Related tools by DataKiln

- [Telegram Channel Scraper — posts, views & reactions from public channels](https://apify.com/datakiln/telegram-channel-scraper)
- [YouTube Channel Email Finder — creator emails, socials & stats](https://apify.com/datakiln/youtube-channel-email-finder)
- [YouTube Comments Scraper — comments, replies & likes](https://apify.com/datakiln/youtube-comments-scraper)
- [Podcast Email Finder — host emails from Apple Podcasts RSS feeds](https://apify.com/datakiln/podcast-email-finder)
- [TikTok Profile & Email Finder — bio, stats & contacts](https://apify.com/datakiln/tiktok-profile-email-finder)
- [Website Contact Extractor — emails, phones & socials from any website](https://apify.com/datakiln/website-contact-extractor)

### Support

Found a bug or need a field that's missing? Open an issue on the **Issues** tab. We usually reply within 24 hours.

# Actor input Schema

## `searchQueries` (type: `array`):

Job titles, skills or companies to search for — one search per line, e.g. 'python developer' or 'marketing manager'. Each one is searched in the location below with the filters below.

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

Country, region or city exactly as you'd type it on LinkedIn, e.g. 'United States', 'London', 'Berlin, Germany' or 'Remote'. Leave empty for worldwide.

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

Optional. Paste job search URLs copied from your browser (https://www.linkedin.com/jobs/search/?keywords=…\&location=…\&f_TPR=…). Keywords, location, geoId and all f\_\* filters in the URL are reused as-is; the filters below only fill in what the URL doesn't set. Single job links (https://www.linkedin.com/jobs/view/…) also work.

## `maxJobsPerQuery` (type: `integer`):

How many jobs to collect for each keyword / URL. LinkedIn's public search shows at most ~1,000 results per search — to get more, split it into several searches (different locations, date ranges or filters). 0 = as many as LinkedIn returns.

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

Only jobs posted within this time window.

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

Only jobs with these experience levels. Leave empty for all.

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

Only jobs with these employment types. Leave empty for all.

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

Only on-site, remote or hybrid jobs. Leave empty for all.

## `easyApplyOnly` (type: `boolean`):

Only jobs you can apply to directly on LinkedIn with Easy Apply.

## `sortBy` (type: `string`):

Order of results. 'Most recent' is best for daily monitoring.

## `fetchJobDetails` (type: `boolean`):

Open every job to get the full description (text + HTML), seniority level, employment type, job function, industries, applicant count and salary when shown. Turn off for a faster, card-only scrape (title, company, location, date).

## `maxConcurrency` (type: `integer`):

How many job pages to open at the same time. Higher is faster but more likely to be rate-limited by LinkedIn.

## `proxyConfiguration` (type: `object`):

Apify datacenter proxy is used by default and works for LinkedIn's public job pages. Each retry uses a new IP.

## Actor input object example

```json
{
  "searchQueries": [
    "python developer"
  ],
  "location": "United States",
  "maxJobsPerQuery": 50,
  "datePosted": "any",
  "easyApplyOnly": false,
  "sortBy": "relevance",
  "fetchJobDetails": true,
  "maxConcurrency": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

All jobs as JSON items.

## `overview` (type: `string`):

Overview table view.

# 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 = {
    "searchQueries": [
        "python developer"
    ],
    "location": "United States",
    "maxJobsPerQuery": 50,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("datakiln/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 = {
    "searchQueries": ["python developer"],
    "location": "United States",
    "maxJobsPerQuery": 50,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("datakiln/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 '{
  "searchQueries": [
    "python developer"
  ],
  "location": "United States",
  "maxJobsPerQuery": 50,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call datakiln/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datakiln/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/B8sAdndLiunfmztkJ/builds/mjvVDZjmoEkVjuQVx/openapi.json