# LinkedIn Jobs Scraper (`neuro-scraper/linkedin-jobs-scraper`) Actor

LinkedIn Jobs Scraper SD - LinkedIn Jobs Scraper is a job data tool that extracts public LinkedIn job postings by keyword and location: title, company, location, date, applicants, seniority, employment type, industries and full description. No login.

- **URL**: https://apify.com/neuro-scraper/linkedin-jobs-scraper.md
- **Developed by:** [Neuro Scraper](https://apify.com/neuro-scraper) (community)
- **Categories:** Jobs
- **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.49 / 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/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 — public LinkedIn job postings, no login

The LinkedIn Jobs Scraper reads LinkedIn's public, logged-out job search and job pages and returns one row per job: title, company, location, posted date, applicants, seniority level, employment type, industries, salary (when the job page shows one) and the full description.

It reads only the guest job pages anyone can open without an account. No login, no cookies, no profiles, no company pages.

#### Input

| Field | Type | Default | Meaning |
|---|---|---|---|
| `keywords` | list | `python developer` (prefill) | One LinkedIn job search per line |
| `location` | text | `United States` (prefill) | Where to search, as typed on LinkedIn; empty = worldwide |
| `startUrls` | URLs | – | LinkedIn job search URLs (filters in them are used) or single job URLs (`/jobs/view/<id>/`) |
| `timePosted` | select | `any` | Past 24 hours / week / month — LinkedIn's own filter |
| `jobTypes` | multi-select | – | Full-time, Part-time, Contract ... — checked against each job page's "Employment type" |
| `experienceLevels` | multi-select | – | Internship ... Executive — checked against each job page's "Seniority level" |
| `remoteOnly` | boolean | `false` | Keep jobs whose title, location or description mentions remote work (text check) |
| `easyApplyOnly` | boolean | `false` | LinkedIn's own Easy Apply filter |
| `companyIds` | list | – | LinkedIn numeric company IDs (the `f_C=` value of a LinkedIn search URL) |
| `scrapeDetails` | boolean | `true` | Open each job page (description, applicants, criteria, salary) |
| `maxItems` | integer | `20` | Stop after this many jobs |
| `proxyConfiguration` | proxy | Apify RESIDENTIAL | Proxy for LinkedIn |

A job URL given in `startUrls` is always returned; the filters apply to search results.

#### Output

| Field | Meaning |
|---|---|
| `jobId`, `jobUrl` | LinkedIn job ID and `https://www.linkedin.com/jobs/view/<id>/` |
| `title`, `companyName`, `companyUrl`, `companyLogo` | From the search card / job page |
| `location`, `postedDate`, `postedTimeAgo`, `badge` | Card location, date (YYYY-MM-DD), "1 week ago", "Actively Hiring" |
| `salary` | "Base pay range ..." when the job page shows it |
| `applicantsCount`, `applicantsText` | `66` for "66 applicants"; `200` for "Over 200 applicants" (a lower bound); empty for "Be among the first 25 applicants" |
| `seniorityLevel`, `employmentType`, `industries` | The job page's criteria list |
| `applyType` | `easyApply` or `offsite` (the off-site apply link is behind LinkedIn sign-in) |
| `descriptionText`, `descriptionHtml` | Full description |
| `remoteMentioned` | Title, location or description mentions remote work |
| `searchKeywords`, `searchLocation`, `searchUrl`, `scrapedAt` | The search that produced the row, UTC time |

With `scrapeDetails` off, rows hold the card fields only (no salary, applicants, criteria, description).

#### Measured (2026-10-03, one residential IP, no proxy)

| Test | Result |
|---|---|
| `python developer` / United States, 20 jobs with details | 20 rows in 41 s, 2 search pages + 20 job pages, every request HTTP 200 |
| `data engineer` / United States, past week, 120 jobs, no details | 120 rows in 23 s from 12 pages; every posted date within the week |
| Nurse search URL (London, past week) + job URL, full-time + 3 seniority levels | 8 matching rows in 423 s: 22 search pages, 207 job pages dropped by the filters |
| Job URL + `software engineer` remote only | 4 rows in 28 s (job URL kept, 3 remote jobs, 8 dropped) |
| Bad URLs / empty input | Clean stop with an error line per input |

#### Limits (measured)

- One search reaches about 990 jobs: `start=990` came back empty and `start=1000` answered HTTP 400. Split big searches by location or time posted.
- Logged out, LinkedIn ignores its job-type (`f_JT`), experience (`f_E`), remote (`f_WT`) and distance filters: the results were identical with and without them. The Actor therefore checks job type and seniority on each job page and remote work by text. Most jobs say "Not Applicable" for seniority (15 of 20 in our default test), so seniority filters can need many job pages.
- LinkedIn's guest job page no longer shows "Job function" (0 of 20 jobs). Salary was on 5 of 20 job pages and on 0 of 140 search cards.
- LinkedIn throttles heavy traffic (HTTP 429 / 999). None appeared in our ~300 requests at 1.2–2.4 s spacing. On a throttle the Actor waits, opens a new session (a new proxy IP on Apify) and stops that search after 3 tries.

#### Terms note

LinkedIn's User Agreement (section 8.2) prohibits scraping and automated access to its services. Its robots.txt asks for permission before automated access, and its Googlebot rules disallow `/jobs-guest/`.

In hiQ Labs v. LinkedIn the Ninth Circuit (2022) found scraping public pages is likely not "unauthorized access" under the CFAA. The district court then found hiQ had breached LinkedIn's User Agreement, and the case ended in a 2022 consent judgment.

This Actor reads only public, logged-out job postings, slowly, and collects no member profiles. You are responsible for how you use it and the data.

#### Example input

```json
{"keywords": ["data engineer"], "location": "United States", "timePosted": "pastWeek", "maxItems": 100, "scrapeDetails": false}
```

# Actor input Schema

## `keywords` (type: `array`):

One LinkedIn job search per line, e.g. "python developer" or "registered nurse". Combined with the location below.

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

Where to search, as you would type it on LinkedIn: "United States", "London, England, United Kingdom", "Berlin". Leave empty for worldwide.

## `startUrls` (type: `array`):

Paste LinkedIn job search URLs (https://www.linkedin.com/jobs/search?keywords=...\&location=...\&f_TPR=r86400) or single job URLs (https://www.linkedin.com/jobs/view/4431992044/). Search URL filters are used as given.

## `timePosted` (type: `string`):

Only jobs posted within this time (LinkedIn's own filter).

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

Keep only these employment types. Checked against the "Employment type" shown on each LinkedIn job page (LinkedIn ignores this filter for logged-out searches, measured).

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

Keep only these seniority levels, checked against the "Seniority level" on each job page.

## `remoteOnly` (type: `boolean`):

Keep only jobs whose title, location or description mentions remote work. LinkedIn does not show its remote label to logged-out visitors, so this is a text check.

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

Only jobs with LinkedIn Easy Apply (LinkedIn's own filter).

## `companyIds` (type: `array`):

Only jobs of these companies - LinkedIn's numeric company IDs, e.g. 1035 (Microsoft). Find them in a LinkedIn job search URL after f_C=.

## `scrapeDetails` (type: `boolean`):

Read each job's page for the full description, applicants, seniority level, employment type, job function and industries (one extra request per job). Off = search-card fields only, about 10x faster.

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

Stop after this many jobs in total. One LinkedIn search reaches at most about 990 jobs.

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

Residential proxy is recommended and is the default.

## Actor input object example

```json
{
  "keywords": [
    "python developer"
  ],
  "location": "United States",
  "timePosted": "any",
  "remoteOnly": false,
  "easyApplyOnly": false,
  "scrapeDetails": true,
  "maxItems": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# 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": [
        "python developer"
    ],
    "location": "United States",
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("neuro-scraper/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 = {
    "keywords": ["python developer"],
    "location": "United States",
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuro-scraper/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/4s2cwgH8rOU8BBpJU/builds/7XYMelazqGrdoUfAp/openapi.json