# LinkedIn Jobs Scraper — full descriptions, normalized pay (`greyridge-signals/linkedin-jobs-scraper`) Actor

Search LinkedIn public job postings and get clean, deduped results: title, company, location, remote flag, normalized salary, employment type, seniority, posting date, apply URL and full description. Public guest postings only. Maintained to stay green as LinkedIn changes. Pay per event.

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

## Pricing

from $1.50 / 1,000 job 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

Search **LinkedIn's public job postings** and get back **clean, deduped, fully-normalized
results** — in one stable schema you can load straight into a database, an ATS, or a
job-matching model. No cookies, no login, no scraping code to maintain on your side.

Built and kept green by **Grey Ridge** — when LinkedIn changes its page shape or rate
limits harder, we fix the extractor and tune the proxy strategy so your pipeline doesn't
break.

### What you get per job

| Field | Example |
|---|---|
| `title` | `Software Engineer II (Java/AWS)` |
| `company` | `JPMorganChase` |
| `location` | `New York, NY` |
| `remote` | `true` |
| `employment_type` | `Full-time` |
| `seniority_level` | `Mid-Senior level` (with `fullDescription`) |
| `industries` | `Financial Services` (with `fullDescription`) |
| `department` | `Engineering` (LinkedIn job function, with `fullDescription`) |
| `salary` | `USD123500 - USD150000 / year` |
| `salary_min` / `salary_max` | `123500` / `150000` |
| `salary_currency` / `salary_period` | `USD` / `year` |
| `posted_at` | `2026-10-08T00:00:00.000Z` (ISO, from LinkedIn's `datetime` attribute) |
| `url` | `https://www.linkedin.com/jobs/view/…` (canonical, tracking params stripped) |
| `job_key` | `4476983365` (LinkedIn's numeric job id — use it to dedupe across runs) |
| `description_text` / `description_html` | full job description (with `fullDescription`) |
| `source_platform` | `linkedin` |

Every result is deduped on LinkedIn's numeric job id within a run, so you never pay for the
same posting twice.

### Input

```json
{
  "keywords": "software engineer",
  "location": "United States",
  "remoteOnly": true,
  "datePosted": "week",
  "experienceLevel": "mid-senior level",
  "jobType": "full-time",
  "fullDescription": true,
  "maxResults": 200
}
```

- **`keywords`** / **`location`** — provide at least one (or a `company` / `companyId`).
- **`geoId`** — LinkedIn's numeric geo id for an exact-location match (optional).
- **`remoteOnly`** — restrict to remote (LinkedIn workplace-type = Remote).
- **`datePosted`** — `past24h` · `week` · `month`.
- **`experienceLevel`** — internship · entry level · associate · mid-senior level · director · executive.
- **`jobType`** — full-time · part-time · contract · temporary · internship · volunteer.
- **`company`** / **`companyId`** — narrow to a company by name, or an exact feed by LinkedIn company id.
- **`sortBy`** — `relevance` (default) or `date` (most recent first).
- **`fullDescription`** — fetch each job's detail page for the complete description, salary,
  seniority, job function and industries (slower, more proxy traffic).
- **`maxResults`** — hard cap that bounds your cost; you know your maximum spend before the run.

### Salary normalization

LinkedIn shows compensation as free text in several shapes — `"$123,500.00/yr -
$150,000.00/yr"`, `"$55.00/hr"`, `"€4,000/mo - €5,000/mo"`, `"From $80,000/yr"`,
`"Base pay range $120K/yr - $150K/yr"`. We parse all of them into structured
`salary_min` / `salary_max` / `salary_currency` / `salary_period`, so you can filter and
compare across postings without writing your own parser.

### Reliability

LinkedIn's public job pages rate-limit aggressively (HTTP 429 and LinkedIn's signature
`999` status) once a single IP pulls hard — which is why self-built LinkedIn scrapers rot
and why half-maintained ones drift to low ratings. This actor:

- escalates proxy tier only when needed (datacenter first, residential on a block) to keep
  runs cheap;
- aborts a run early with a circuit breaker if the block-rate spikes, rather than burning
  your usage on an unwinnable pull;
- is monitored and patched when LinkedIn changes its markup or tightens limits.

### Pricing

**Pay per event — priced per job returned.** You pay only for jobs actually returned;
rate-limited or blocked pages cost nothing. `maxResults` is your hard ceiling — set it and
you know your maximum spend before the run starts. Billing is event-based, so autonomous
agents can call and pay for this actor per request.

### Try it free (no account)

The bundled CLI fetches LinkedIn's public postings live for small pulls — no account, no
key — and also parses pages you've already saved:

```bash
npx linkedin-jobs search "software engineer" --location "United States" --remote --max 25 --pretty
npx linkedin-jobs search "data scientist" --since week --full          # with full descriptions
npx linkedin-jobs detail 4476983365                                    # one job id -> detail
npx linkedin-jobs parse saved-search.html --pretty                     # parse a saved page
```

For high volume and always-green reliability (rotating residential proxy, retries, circuit
breaker), use this actor.

### Same schema as our Indeed & Multi-ATS Jobs Scrapers

The field names here match our **Indeed Jobs Scraper** and **Multi-ATS Jobs Scraper**
(Greenhouse, Lever, Ashby, Workday, SmartRecruiters, Recruitee, Workable) exactly — so you
can merge LinkedIn results with Indeed and direct-from-ATS results in **one table** with no
remapping. That unified cross-source schema is unique on the store: together the three
actors are a single jobs-data layer.

### Scope & notes

- **Public guest job postings only.** No login, no authenticated/member-area data, no
  personal profile data — only the fields LinkedIn publishes openly on a job post.
- `posted_at` comes from LinkedIn's own `datetime` attribute, falling back to a best-effort
  ISO date resolved from relative text (`"3 weeks ago"`).
- `seniority_level`, `industries`, `department` and the full description require
  `fullDescription` (they live on the detail page, not the search card).
- Very broad searches are bounded by `maxResults`.

# Actor input Schema

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

Search terms, e.g. "software engineer", "product manager python". Combine with location for best results.

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

City, region or country, e.g. "United States", "London", "Remote".

## `geoId` (type: `string`):

LinkedIn's numeric geo identifier for an exact location match. Overrides the free-text location when set.

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

Restrict to remote postings (LinkedIn workplace-type = Remote).

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

Only postings newer than this window.

## `experienceLevel` (type: `string`):

Filter by experience level.

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

Filter by employment type.

## `company` (type: `string`):

Narrow results to a company by name (added to the search). For an exact company feed use companyId.

## `companyId` (type: `string`):

LinkedIn's numeric company id (f_C) for an exact company job feed.

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

Relevance (default) or most recent.

## `maxResults` (type: `integer`):

Maximum number of jobs to return (one billable result per job). Bounds COGS.

## `fullDescription` (type: `boolean`):

Fetch each job's detail page for the full description, salary, seniority and industries. Slower and uses more proxy traffic.

## Actor input object example

```json
{
  "keywords": "software engineer",
  "location": "United States",
  "remoteOnly": false,
  "datePosted": "",
  "experienceLevel": "",
  "jobType": "",
  "sortBy": "relevance",
  "maxResults": 100,
  "fullDescription": false
}
```

# Actor output Schema

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

The normalized rows this run produced, in the default dataset.

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

Open the run results in the Apify Console.

# 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",
    "location": "United States"
};

// Run the Actor and wait for it to finish
const run = await client.actor("greyridge-signals/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",
    "location": "United States",
}

# Run the Actor and wait for it to finish
run = client.actor("greyridge-signals/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",
  "location": "United States"
}' |
apify call greyridge-signals/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,greyridge-signals/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/PiQ59cUfdkN6l2odB/builds/wuZ12yAl5VhQiZyFk/openapi.json