# LinkedIn Jobs Search — No Login, Full Job Details (`arpitgandhi1934/linkedin-jobs-search`) Actor

Search LinkedIn job listings by keyword + location. Pure public API, no account or cookie needed. Returns title, company, location, posted date, seniority, employment type, job function, industries, applicants, and full job description.

- **URL**: https://apify.com/arpitgandhi1934/linkedin-jobs-search.md
- **Developed by:** [Arpit Gandhi](https://apify.com/arpitgandhi1934) (community)
- **Categories:** Lead generation, Jobs, Automation
- **Stats:** 2 total users, 1 monthly users, 91.7% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.09 / 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/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## 💼 LinkedIn Jobs Search — No Login, Full Job Details

**Search LinkedIn jobs and get rich, structured data — no LinkedIn account, no cookies, no login. Ever.** ⚡

Give it a job title and a location. Get back clean JSON with everything a job seeker or recruiter actually cares about: salary, seniority, apply type, freshness, company info, and the full description. Fast, reliable, and built on LinkedIn's own public job data.

***

### ✨ Why this scraper?

| | |
|---|---|
| 🔓 **No login required** | No account, no cookie, no session token to expire. Nothing to get banned. |
| 🧾 **30+ fields per job** | Salary, seniority, apply type, applicants, poster, company size & website, and more. |
| ⚡ **Fast** | Parallel fetching — ~40 jobs in seconds. |
| 💰 **Smart salary detection** | Reads the listed salary *and* pulls pay ranges out of the description when LinkedIn hides them. |
| 🎯 **Powerful filters** | Date posted, remote/hybrid/on-site, job type, experience level. |
| 🌍 **Any location, any role** | Works worldwide — city, region, or whole country. |

***

### 🚀 Quick start

1. Enter a **job title / keywords** (e.g. `real estate analyst`) 🔎
2. Enter a **location** (e.g. `Toronto, Ontario, Canada`) 📍
3. Click **Start** ▶️

That's it. Results stream into the dataset — export to JSON, CSV, Excel, or pull them via API.

***

### 📥 Sample input

```json
{
  "keywords": "software engineer",
  "location": "San Francisco, California, United States",
  "maxJobs": 50,
  "enrich": true,
  "enrichCompany": true,
  "datePosted": "week",
  "workplace": "remote",
  "jobType": "full-time",
  "experience": "mid-senior"
}
```

#### ⚙️ Input options

| Field | What it does | Example |
|---|---|---|
| `keywords` ⭐ | Job title or search terms (**required**) | `"software engineer"` |
| `location` | City, region, or country. Blank = worldwide | `"San Francisco, CA"` |
| `maxJobs` | How many jobs to return (up to ~1000) | `50` |
| `enrich` | Fetch each job's full detail page (description, salary, seniority…) | `true` |
| `enrichCompany` | Also fetch company description, website & employee count | `false` |
| `datePosted` | `any` · `month` · `week` · `day` | `"week"` |
| `workplace` | `any` · `on-site` · `remote` · `hybrid` | `"remote"` |
| `jobType` | `any` · `full-time` · `part-time` · `contract` · `temporary` · `internship` | `"full-time"` |
| `experience` | `any` · `entry-level` · `associate` · `mid-senior` · `director` · `executive` | `"mid-senior"` |
| `concurrency` | Parallel requests — higher = faster (default 20) | `20` |

***

### 📤 Sample output

Each job is one record like this 👇

```json
{
  "id": "4437461678",
  "link": "https://www.linkedin.com/jobs/view/software-engineer-early-career-at-notion-4437461678",
  "title": "Software Engineer, Early Career",
  "companyName": "Notion",
  "companyLinkedinUrl": "https://www.linkedin.com/company/notionhq",
  "companyLogo": "https://media.licdn.com/dms/image/v2/D4E0BAQGwvcv_1tHZ4w/company-logo_100_100/...",
  "location": "San Francisco, CA",
  "workplaceType": null,
  "isRemote": false,
  "salaryInfo": ["$130,000", "$150,000"],
  "salarySource": "description",
  "postedAt": "2026-07-06",
  "postedText": "4 days ago",
  "postedDaysAgo": 5,
  "benefits": ["Actively Hiring"],
  "applicantsCount": "200",
  "applyType": "company-site",
  "applyUrl": "",
  "isActive": true,
  "reposted": false,
  "seniorityLevel": "Not Applicable",
  "employmentType": "Full-time",
  "jobFunction": "Engineering and Information Technology",
  "industries": "Software Development",
  "jobPosterName": null,
  "jobPosterTitle": null,
  "jobPosterPhoto": null,
  "jobPosterProfileUrl": null,
  "descriptionText": "Who We Are — Notion is the collaborative AI workspace where teams and agents think together...",
  "descriptionHtml": "<p>Who We Are</p><p>Notion is the collaborative AI workspace...</p>",
  "companyDescription": "Notion blends your everyday work tools into one. Product roadmap? Company wiki? Meeting notes?...",
  "companyWebsite": "https://notion.com",
  "companyEmployeesCount": 7730
}
```

***

### 🗂️ Every field explained

#### 🧭 Job basics

| Field | Description |
|---|---|
| `id` | LinkedIn job posting ID |
| `link` | Direct URL to the job posting |
| `title` | Job title |
| `location` | Job location as shown on LinkedIn |
| `workplaceType` | `Remote` · `Hybrid` · `On-site` (when detectable) |
| `isRemote` | `true` if the role is remote |

#### 💵 Pay & freshness

| Field | Description |
|---|---|
| `salaryInfo` | Pay range as `[min, max]` (e.g. `["$130,000", "$150,000"]`) |
| `salarySource` | `listed` (official field) or `description` (parsed from the text) |
| `postedAt` | Date posted (`YYYY-MM-DD`) |
| `postedText` | Human text, e.g. `"4 days ago"` |
| `postedDaysAgo` | Days since posted, as a number — great for sorting by freshness ⏱️ |
| `benefits` | Badges like `"Actively Hiring"` |

#### 📨 Applying

| Field | Description |
|---|---|
| `applicantsCount` | Number of applicants |
| `applyType` | `easy-apply` (apply on LinkedIn) or `company-site` (apply on the employer's site) |
| `applyUrl` | External apply link when LinkedIn exposes it |
| `isActive` | `false` if the listing is no longer accepting applications ⛔ |
| `reposted` | `true` if the listing was reposted |

#### 🏷️ Classification

| Field | Description |
|---|---|
| `seniorityLevel` | e.g. `Associate`, `Mid-Senior`, `Director` |
| `employmentType` | `Full-time`, `Contract`, `Internship`… |
| `jobFunction` | e.g. `Engineering and Information Technology` |
| `industries` | e.g. `Software Development` |

#### 👤 Job poster (when available)

| Field | Description |
|---|---|
| `jobPosterName` | Name of the recruiter / hiring manager who posted |
| `jobPosterTitle` | Their job title |
| `jobPosterPhoto` | Their profile photo URL |
| `jobPosterProfileUrl` | Their LinkedIn profile URL |

#### 📝 Descriptions

| Field | Description |
|---|---|
| `descriptionText` | Full job description as clean plain text |
| `descriptionHtml` | Full job description with original HTML formatting |

#### 🏢 Company (only when `enrichCompany: true`)

| Field | Description |
|---|---|
| `companyName` | Company name |
| `companyLinkedinUrl` | Company's LinkedIn page |
| `companyLogo` | Company logo image URL |
| `companyDescription` | The company's "About" description |
| `companyWebsite` | Company website |
| `companyEmployeesCount` | Number of employees on LinkedIn |

***

### 💡 Great for

- 🔍 **Job seekers** — build a live, filtered job board with salary & freshness signals
- 🧑‍💼 **Recruiters & sourcers** — track who's hiring and see the poster behind each role
- 📊 **Market research** — salary benchmarking, hiring trends, competitor headcount
- 🤖 **Job boards & AI apps** — feed clean, structured job data into your product

***

### ❓ FAQ

**Do I need a LinkedIn account?**
No. This uses LinkedIn's public job data — no login, no cookies, nothing to configure. 🎉

**Will my account get banned?**
There's no account involved, so there's nothing to ban.

**Why is a salary sometimes empty?**
Not every employer publishes one. When the official field is empty, we still try to recover a range from the description (`salarySource: "description"`). If neither exists, `salaryInfo` is `[]`.

**Why is `applyUrl` sometimes empty?**
For jobs that apply on the company's own website, LinkedIn hides the external link publicly — so we flag it as `applyType: "company-site"` instead. Open the `link` to apply.

**How many jobs can I get?**
LinkedIn's public search tops out around ~1000 results per query. Narrow with filters or split by location to go wider.

***

*Not affiliated with LinkedIn. Scrapes publicly available job data only.*

# Actor input Schema

## `keywords` (type: `string`):

Job title or keywords, e.g. "real estate analyst" or "react developer".

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

Where to search — city, region, or country. E.g. "Toronto, Ontario, Canada" or just "Canada". Leave blank for worldwide.

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

How many jobs to return. LinkedIn's public API caps out around 1000 per query.

## `enrich` (type: `boolean`):

Also fetch each job's detail page: description, salary, seniority, employment type, function, industries, apply type, job poster, active/expired status. Slower but far richer. Off = search cards only (fast).

## `enrichCompany` (type: `boolean`):

Also fetch each company's page for description, website, and employee count. Cached per company. Adds requests — leave off unless you need company data.

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

Only jobs posted within this window.

## `workplace` (type: `string`):

Filter by on-site, remote, or hybrid.

## `jobType` (type: `string`):

Filter by employment type.

## `experience` (type: `string`):

Filter by seniority / experience level.

## `concurrency` (type: `integer`):

How many pages to fetch at once. With the Apify proxy on (default), 20 is fast and clean. Higher = faster; lower only if you run without a proxy and hit rate limits.

## `delayMs` (type: `integer`):

Delay between search-page requests. Detail fetches run in parallel (see Parallel requests).

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

Proxy to route requests through. Recommended (residential) for large runs to avoid IP rate limits.

## Actor input object example

```json
{
  "keywords": "real estate analyst",
  "location": "Toronto, Ontario, Canada",
  "maxJobs": 50,
  "enrich": true,
  "enrichCompany": false,
  "datePosted": "any",
  "workplace": "any",
  "jobType": "any",
  "experience": "any",
  "concurrency": 20,
  "delayMs": 800,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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": "real estate analyst",
    "location": "Toronto, Ontario, Canada",
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("arpitgandhi1934/linkedin-jobs-search").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": "real estate analyst",
    "location": "Toronto, Ontario, Canada",
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("arpitgandhi1934/linkedin-jobs-search").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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": "real estate analyst",
  "location": "Toronto, Ontario, Canada",
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call arpitgandhi1934/linkedin-jobs-search --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=arpitgandhi1934/linkedin-jobs-search",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/xfhSjRWB9JJsV16SG/builds/6oVD6Q50u6fIPe6D9/openapi.json