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

Scrape LinkedIn jobs without login via the public guest API. Search cards plus optional detail enrichment: full description, salary, seniority, employment type, industries, and applicant count. HTTP/1.1 + residential proxy.

- **URL**: https://apify.com/aurenic/linkedin-jobs-scraper.md
- **Developed by:** [Aurenic](https://apify.com/aurenic) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.90 / 1,000 results

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

Scrape LinkedIn jobs without login via the public guest API. Search cards plus optional detail enrichment: full description, salary, seniority, employment type, industries, and applicant count. HTTP/1.1 + residential proxy.

### What does LinkedIn Jobs Scraper do?

Extract jobs from LinkedIn's public guest API in two modes:

- **Search by keywords + location** — returns title, company, location, posted date, and job URL. Optional detail enrichment opens each job page for the **full description, salary, seniority, employment type, industries, and applicant count**.
- **Fetch specific job URLs** — pass direct LinkedIn job URLs and get full detail records.

Unlike most LinkedIn scrapers on the Store, this actor:

- Uses **client-side filtering** for job type, experience level, and remote — because LinkedIn silently ignores `f_JT`, `f_E`, and `f_WT` since 11 September 2026 (returns identical result sets regardless of the parameter value).
- Runs on **HTTP/1.1 via got-scraping** — LinkedIn's edge blocks HTTP/2 fingerprints regardless of headers.
- **Rotates residential proxy sessions** every N requests, well under LinkedIn's 50–100 request per-IP rate limit.

### Output fields

#### Job detail (default when `fetchDetails: true`)

| Field | Description |
|---|---|
| jobId | LinkedIn numeric job ID |
| url | Canonical job URL |
| title | Job title |
| company | Hiring company |
| location | Location string |
| description | Full job description (plain text) |
| descriptionHtml | Full description (HTML) |
| descriptionLength | Char count |
| seniority | Seniority level (from criteria block) |
| employmentType | Full-time, Part-time, Contract, etc. |
| jobFunction | Job function |
| industries | Industry list |
| salaryText | Salary string when disclosed |
| salaryRange | Structured salary range when available |
| applicantsCount | Number of applicants (parsed integer) |
| applicantsRaw | Raw applicant caption |
| isEasyApply | Easy Apply flag |
| applyUrl | Apply button target |
| postedAgo | Relative posted date |
| criteria | Full criteria block as a map |
| jsonLd | Structured JobPosting JSON-LD when present |

#### Job card (when `fetchDetails: false`)

| Field | Description |
|---|---|
| jobId / url | Identity |
| title / company / location | Core fields |
| postedAt / postedAgo | Posted date |
| companyLogo | Logo URL |

### Who is it for?

- **Recruiters and talent-sourcing teams** tracking competitor hiring and building candidate pipelines
- **Job board aggregators** feeding LinkedIn listings into their own products
- **Market researchers** analyzing salary trends, applicant competition, and skill demand
- **Career coaches and job seekers** monitoring specific roles across companies
- **AI/ML builders** sourcing job descriptions for training or RAG pipelines
- **Sales teams** identifying companies with active hiring signals

### Pricing

**$0.90 per 1,000 results.** No subscription.

| Results | Cost |
|---|---|
| 100 | $0.09 |
| 1,000 | $0.90 |
| 10,000 | $9.00 |

### How to use it

1. Pick a **Mode**.
2. For search: enter **Keywords** and optionally **Locations**.
3. Optionally set **Posted Within** (the only server-side filter that still works).
4. Set **Fetch Full Details** on to get description + salary + applicants.
5. Optionally apply **Job Type** / **Experience Level** / **Remote Only** client-side filters.
6. Click **Start**.

### Output example

```json
{
  "recordType": "job-detail",
  "jobId": "3847291023",
  "url": "https://www.linkedin.com/jobs/view/3847291023/",
  "title": "Senior Software Engineer",
  "company": "Stripe",
  "location": "San Francisco, CA",
  "description": "We're looking for a senior engineer to join the Payments Infrastructure team. You'll design, build, and operate the systems that move billions of dollars...",
  "descriptionLength": 2847,
  "seniority": "Mid-Senior level",
  "employmentType": "Full-time",
  "jobFunction": "Engineering",
  "industries": "Financial Services",
  "salaryText": "$180,000/yr - $250,000/yr",
  "salaryRange": "$180K/yr - $250K/yr",
  "applicantsCount": 142,
  "applicantsRaw": "142 applicants",
  "isEasyApply": false,
  "applyUrl": "https://stripe.com/jobs/apply/...",
  "postedAgo": "2 days ago",
  "criteria": {
    "Seniority level": "Mid-Senior level",
    "Employment type": "Full-time",
    "Job function": "Engineering",
    "Industries": "Financial Services"
  },
  "searchKeyword": "software engineer",
  "searchLocation": "United States",
  "scrapedAt": "2026-09-26T12:00:00.000Z"
}
```

### Technical details

- **LinkedIn public guest API** — `https://www.linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search` and `/jobs-guest/jobs/api/jobPosting/{id}`. No login, no cookies, no account.
- **HTTP/1.1 required** — LinkedIn's edge blocks HTTP/2 fingerprints even with browser headers. The actor uses `got-scraping` with `http2: false`.
- **Residential proxy mandatory** — datacenter IPs hit 429 after 50–100 requests. The actor rotates sessions every 40 requests by default.
- **Server-side filter caveat** — as of 11 September 2026, LinkedIn silently ignores `f_JT` (job type), `f_E` (experience), `f_WT` (remote), and `sortBy`. **Only `f_TPR` (posted within) and `f_AL` (easy apply) still change the result set.** The actor handles this by scanning extra pages and filtering client-side.
- **Scan cap logic** — with rare filters (e.g. contract-only), the actor scans up to `maxJobs × maxScanMultiplier` cards (capped at 500) so filters with <10% hit rate still return matches. Non-matching jobs cost nothing.
- **No browser, no login** — pure HTTP + Cheerio.

### Known limits

- **Residential proxy bandwidth is real cost.** Detail mode adds one request per job. For 1,000 jobs, budget ~1,000 extra proxy requests.
- **`f_JT`, `f_E`, `f_WT` are broken server-side.** The actor applies these client-side, which means scanning more pages than the result count suggests. Rare filters (contract, entry level) can require 5–10× the scan volume.
- **Some listings don't show salary or applicant count.** Those fields return empty strings / null. This is a LinkedIn source limitation, not an actor bug.
- **Search returns ~25 cards per page.** Pagination is via `start` incrementing by 25. LinkedIn caps deep pages at around 1,000 results per query.
- **`postedWithin` uses LinkedIn's `rXXX` format** — `r86400` (24h), `r604800` (7d), `r2592000` (30d).
- **Applicant counts can be coarse.** LinkedIn shows "Over 200 applicants" for high-volume roles; the actor returns `null` in that case (no numeric to parse).
- **Job cards may duplicate across pages.** The actor dedupes by `jobId`.

### FAQ

**Do I need a LinkedIn account?** No. Public guest endpoints only — no login, no cookies, no risk to your account.

**Do I need a proxy?** Yes. Residential proxy is pre-configured and required — LinkedIn rate-limits datacenter IPs after ~50 requests.

**Why do job-type filters sometimes return nothing?** LinkedIn silently ignores `f_JT`. The actor filters client-side, which means scanning many pages. With a very rare filter (e.g. `contract` on a keyword with mostly full-time roles), you may hit the scan cap before finding matches. Raise `maxScanMultiplier` or broaden the keyword.

**Why is the run slow?** Two reasons: (1) LinkedIn rate-limits, so the actor defaults to 2.5s between requests; (2) detail mode adds one request per job. 500 jobs at full detail ≈ 25 minutes.

**Can I fetch jobs by URL?** Yes — use detail mode with an array of LinkedIn job URLs.

**How do I export data?** After a run, go to Storage → Export as JSON, CSV, Excel.

### Support

Open an issue on the Actor's page for bugs or feature requests.

# Actor input Schema

## `mode` (type: `string`):

What to scrape.

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

Job title or search terms (e.g. 'software engineer', 'data analyst', 'product manager').

## `locations` (type: `array`):

Cities, states, or countries (e.g. 'New York, NY', 'United States', 'Remote', 'Germany'). Leave empty for any.

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

Only jobs posted within this window. THIS FILTER STILL WORKS post-2026-09-11 (unlike f\_JT/f\_E/f\_WT).

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

Only return jobs with LinkedIn Easy Apply.

## `fetchDetails` (type: `boolean`):

Open every job card and extract full description, salary, seniority, employment type, industries, and applicant count. One extra request per job (uses residential proxy bandwidth).

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

Filter to specific employment types: Full-time, Part-time, Contract, Temporary, Internship. Applied AFTER detail fetch — LinkedIn now silently ignores server-side job-type filters.

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

Filter by seniority level: Entry level, Associate, Mid-Senior level, Director, Executive, Internship.

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

Only keep jobs whose location contains 'remote'.

## `jobUrls` (type: `array`):

Direct LinkedIn job URLs (e.g. https://www.linkedin.com/jobs/view/3847291023). Used in detail mode.

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

Hard cap on returned jobs per run. Default 30 keeps test runs under 3 minutes given LinkedIn's aggressive rate-limiting.

## `maxScanMultiplier` (type: `integer`):

When client-side filters are active, scan up to (maxJobs × this) cards to find enough matches. Rare filters (e.g. contract-only) need a higher multiplier. Capped at 500 scans.

## `requestDelayMs` (type: `integer`):

Delay between requests. LinkedIn rate-limits aggressively (HTTP 429/451 after 50-100 requests per IP). Default 4000ms is safe; lower only if you have spare proxy bandwidth.

## `sessionRotateEvery` (type: `integer`):

Force a residential proxy IP change after this many requests. LinkedIn flags pagination with HTTP 451 — 15 is aggressive but reliable.

## Actor input object example

```json
{
  "mode": "search",
  "keywords": [
    "software engineer"
  ],
  "locations": [
    "United States"
  ],
  "postedWithin": "",
  "easyApplyOnly": false,
  "fetchDetails": true,
  "jobTypes": [],
  "experienceLevels": [],
  "remoteOnly": false,
  "jobUrls": [],
  "maxJobs": 30,
  "maxScanMultiplier": 5,
  "requestDelayMs": 4000,
  "sessionRotateEvery": 15
}
```

# Actor output Schema

## `results` (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": [
        "software engineer"
    ],
    "locations": [
        "United States"
    ],
    "jobTypes": [],
    "experienceLevels": [],
    "jobUrls": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("aurenic/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": ["software engineer"],
    "locations": ["United States"],
    "jobTypes": [],
    "experienceLevels": [],
    "jobUrls": [],
}

# Run the Actor and wait for it to finish
run = client.actor("aurenic/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": [
    "software engineer"
  ],
  "locations": [
    "United States"
  ],
  "jobTypes": [],
  "experienceLevels": [],
  "jobUrls": []
}' |
apify call aurenic/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,aurenic/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/aJrkypIrLjQGXgYY8/builds/Q9pGsTJJ8fLHyGTDa/openapi.json