# LinkedIn Internship Jobs Intelligence (`neuton/linkedin-internship-jobs-intelligence`) Actor

Find public LinkedIn internship and co-op jobs with direct evidence for early-talent recruiting and research.

- **URL**: https://apify.com/neuton/linkedin-internship-jobs-intelligence.md
- **Developed by:** [Neuton Scripts](https://apify.com/neuton) (community)
- **Categories:** Jobs, Lead generation
- **Stats:** 7 total users, 3 monthly users, 81.8% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$12.00 / 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 Internship Jobs Intelligence

Requests are paced with a two-second gap between detail pages. Rate-limit responses use bounded exponential backoff and respect `Retry-After`; long cooldowns are reported as incomplete fetches instead of retried early. Check `RUN_SUMMARY.completed`, `partial`, and `failedRequests` before relying on a complete sample. Only complete, evidence-backed rows are billed.

Find public LinkedIn internship and co-op jobs with direct evidence for early-talent recruiting and research. Built for university career teams, early-talent recruiters, job boards, and workforce researchers.

[Open the one-result software-internship Task](https://apify.com/neuton/linkedin-internship-jobs-intelligence/examples/sample-li-internship-jobs-software-internships?utm_source=apify_store\&utm_medium=actor_readme\&utm_campaign=linkedin_internship_activation\&utm_content=software_internship_task) to inspect an editable US search before running. The maximum Actor charge is `$0.012` when one evidence-backed internship row is returned; rejected, duplicate, unavailable, and diagnostic rows are free.

### What you get

- Public job ID, title, company, location, posting date, and canonical LinkedIn job URL
- Public description, criteria, compensation text, and apply URL when LinkedIn exposes them
- `classification`, `evidenceField`, and `evidenceText` on every returned row
- HTTP-only 256 MB runtime with bounded retries and safe limits
- JSON, CSV, Excel, API, webhook, Task, and MCP-ready output

### Use cases

- Build focused recruiting and talent-research feeds for university career teams, early-talent recruiters, job boards, and workforce researchers
- Monitor public demand by role and location without collecting private profiles
- Add evidence-backed LinkedIn job intelligence to sales, research, and AI-agent workflows

### Choose this Actor when

Use this Actor when you need internship and co-op rows already backed by public evidence. If you only need a large unfiltered list of job cards, start with [LinkedIn Jobs Search Scraper](https://apify.com/neuton/linkedin-jobs-search-scraper). If you already have job IDs or URLs, use [LinkedIn Job Details Scraper](https://apify.com/neuton/linkedin-job-details-scraper).

### Example input

```json
{
  "queries": [
    "software engineering intern"
  ],
  "locations": [
    "United States"
  ],
  "datePosted": "",
  "maxResultsPerQuery": 25
}
```

### First run checklist

1. Keep the default 25-job inspection limit and one query/location pair.
2. Verify `classification`, `evidenceField`, `evidenceText`, and `jobUrl` in the Dataset.
3. Check `RUN_SUMMARY` for jobs scanned, rows saved, billable rows, and failed requests.
4. Expand the limit or schedule the Task only after the evidence matches your workflow.

### Evidence and billing

The Actor returns a row only when the public title, job criteria, location, compensation, or description directly supports the classification. It never guesses sponsorship, seniority, job type, or hiring intent. Diagnostics, incomplete fetches, duplicates, unsupported classifications, and empty results are never billed.

`RUN_SUMMARY` is a free diagnostic record outside the Dataset. It is never a billable result row.

If requests fail or return incomplete pages and no usable row is saved, the run fails with details in `RUN_SUMMARY`. A valid empty search returns zero rows without inventing results. If some complete rows are saved before a failure, the summary reports `completed: false` and `partial: true`; only the complete saved rows are billable. A title match alone is not billed when the requested job-detail page lacks its description.

### Automation and AI agents

Save common searches as Apify Tasks, schedule recurring runs, send results to a webhook, or call this Actor from ChatGPT, Claude, the Neuton Actors MCP server, n8n, Make, Zapier, Clay, a CRM, or a data warehouse. Deduplicate on `jobId` between runs.

### Explore the LinkedIn data family

- [LinkedIn Jobs Search Scraper](https://apify.com/neuton/linkedin-jobs-search-scraper) for broad discovery by role and location
- [LinkedIn Job Details Scraper](https://apify.com/neuton/linkedin-job-details-scraper) for complete records from job IDs or URLs
- [LinkedIn Company Hiring Signals](https://apify.com/neuton/linkedin-company-hiring-signals) for evidence-backed company aggregates
- [LinkedIn Remote Jobs Intelligence](https://apify.com/neuton/linkedin-remote-jobs-intelligence) for verified remote opportunities
- [LinkedIn Salary Jobs Intelligence](https://apify.com/neuton/linkedin-salary-jobs-intelligence) for compensation-bearing postings

### SEO keywords

LinkedIn jobs scraper, LinkedIn jobs API, LinkedIn recruiting data, LinkedIn hiring intelligence, evidence-backed job data, talent market research, recruiting automation, LinkedIn job monitoring, Apify LinkedIn Actor, AI recruiting agent.

### Pricing

Launch PPE price: $12.00 per 1,000 complete evidence-backed results, or about $1.20 for 100. The paid unit is a classified source-backed result, not an unfiltered search card.

### Responsible use

This Actor processes public job-posting information. Do not use it for spam, unlawful discrimination, automated applications, private-profile collection, access-control bypass, or excessive requests. Review LinkedIn's current terms and applicable employment, immigration, and privacy laws before production use. Sponsorship output records public wording and is not legal or immigration advice.

# Actor input Schema

## `queries` (type: `array`):

LinkedIn public-job keywords to inspect.

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

Location text such as United States, London, or Bengaluru.

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

Optional public LinkedIn freshness window. Leave at All dates when relevance matters more than recency.

## `maxResultsPerQuery` (type: `integer`):

Maximum public jobs inspected for each query and location pair.

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

Stop after this many evidence-backed rows are saved.

## Actor input object example

```json
{
  "queries": [
    "software engineering intern"
  ],
  "locations": [
    "United States"
  ],
  "datePosted": "",
  "maxResultsPerQuery": 25,
  "maxItems": 25
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("neuton/linkedin-internship-jobs-intelligence").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("neuton/linkedin-internship-jobs-intelligence").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 '{}' |
apify call neuton/linkedin-internship-jobs-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuton/linkedin-internship-jobs-intelligence"
        }
    }
}
```

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/tjJHPNhyenONocexh/builds/AaA3PbtHlAj89dywz/openapi.json