# Hiring.cafe Scraper — AI-Structured Jobs & Company Data (`haketa/hiring-cafe-scraper`) Actor

Hiring.cafe scraper: AI-structured jobs from thousands of career pages. Extract title, salary, seniority, experience, remote/onsite, skills + company data (funding, size, industry, direct-employer vs agency) and direct apply links. Export JSON, CSV, Excel.

- **URL**: https://apify.com/haketa/hiring-cafe-scraper.md
- **Developed by:** [Haketa](https://apify.com/haketa) (community)
- **Categories:** Jobs, AI, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.50 / 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.
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?

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

## Hiring.cafe Scraper 🧠💼

Extract **AI-structured job listings** from **Hiring.cafe** — a job search engine that aggregates postings from **thousands of company career pages** — without an account or API key. Search anything and get clean JSON, CSV or Excel with data no ordinary job scraper provides:

**structured salary, seniority, years-of-experience, remote/onsite, skills, degree requirements — plus rich company enrichment (funding, size, industry, direct-employer vs agency) and direct apply links.**

Perfect for recruiters, sourcers, B2B sales, labour-market researchers and anyone building a jobs dataset or hiring-signal product.

***

### 🔑 What makes this different

Most job scrapers give you a title, a company and a link. Hiring.cafe listings are **AI-processed**, so each job comes with **90+ structured fields** and **20+ company fields**:

- 💷 **Structured salary** — min/max with period (yearly / monthly / weekly / hourly), when disclosed.
- 🎚️ **Seniority & experience** — seniority level, minimum years of experience, management experience, role type.
- 🌍 **Workplace** — Remote / Hybrid / Onsite, countries, states, cities, "remote worldwide" flag.
- 🧩 **Skills & requirements** — technical tools, languages, degree requirements & fields, a requirements summary and role activities.
- 🏢 **Company enrichment** — employees, year founded, industries, HQ country, organisation type, **funding (type, year, amount, investors)** and **direct-employer vs agency** classification.
- 🔗 **Direct apply URL** and the original source (Greenhouse, Lever, Ashby, Workday, Workable and many more).

***

### 📋 Example output

```json
{
  "id": "greenhouse___acme___abc123",
  "jobTitle": "Senior Software Engineer",
  "companyName": "Acme AI",
  "applyUrl": "https://boards.greenhouse.io/acme/jobs/abc123",
  "source": "grnhse",
  "isExpired": false,
  "location": "San Francisco, California, United States",
  "workplaceType": "Hybrid",
  "workplaceCountries": ["US"],
  "workplaceCities": ["San Francisco, California, US"],
  "isRemoteWorldwide": false,
  "seniorityLevel": "Senior Level",
  "roleType": "Individual Contributor",
  "jobCategory": "Software Engineering",
  "commitment": "Full Time",
  "minYearsExperience": 5,
  "degreeRequirement": { "level": "bachelors", "requirement": "Required", "fields": ["Computer Science"] },
  "technicalTools": ["Python", "AWS", "React"],
  "languageRequirements": ["English"],
  "salaryMin": 160000,
  "salaryMax": 210000,
  "salaryPeriod": "yearly",
  "companyWebsite": "acme.ai",
  "companyEmployees": 250,
  "companyFounded": 2019,
  "companyIndustries": ["Artificial Intelligence", "Software"],
  "companyType": "Private",
  "companyClassification": "direct_employer",
  "companyFundingType": "Series B",
  "companyFundingYear": 2024,
  "companyFundingAmount": "$50M",
  "companyFundingInvestors": ["Sequoia"],
  "searchQuery": "software engineer",
  "scrapedAt": "2026-09-06T15:00:00.000Z",
  "processedJobData": { "...": "all 90+ AI-processed fields" },
  "companyData": { "...": "all 20+ company fields" }
}
```

***

### 🗂️ Fields you get

**Job**

| Field | Description |
|---|---|
| `id`, `jobTitle`, `jobCategory` | Job identity |
| `companyName`, `applyUrl`, `source` | Company, direct apply link, original ATS source |
| `isExpired` | Whether the posting is expired |
| `location`, `workplaceType` | Location and Remote / Hybrid / Onsite |
| `workplaceCountries`, `workplaceStates`, `workplaceCities`, `isRemoteWorldwide` | Where work can happen |
| `seniorityLevel`, `roleType`, `commitment` | Level, IC/manager, full/part-time etc. |
| `minYearsExperience`, `minManagementYoe` | Experience requirements |
| `degreeRequirement`, `technicalTools`, `languageRequirements` | Education, tools, languages |
| `requirementsSummary`, `roleActivities` | AI summary of the role |
| `salaryMin`, `salaryMax`, `salaryPeriod` | Structured pay (when disclosed) |
| `processedJobData` | The full object of 90+ AI-processed fields |

**Company**

| Field | Description |
|---|---|
| `companyWebsite`, `companyEmployees`, `companyFounded` | Basics |
| `companyIndustries`, `companyHqCountry`, `companyType` | Profile |
| `companyClassification` | `direct_employer` vs agency/board |
| `companyFundingType`, `companyFundingYear`, `companyFundingAmount`, `companyFundingInvestors` | Funding signals |
| `companyData` | The full object of 20+ company fields |

***

### 🚀 How to use

1. Click **Try for free**.
2. Enter one or more **Search Queries** — semantic search works great: `software engineer`, `senior product designer remote`, `nurse london`.
3. (Optional) Filter by **Workplace Type** (Remote / Hybrid / Onsite) and **Commitment Type** (Full Time, Contract…).
4. (Advanced) Or apply any filters on hiring.cafe in your browser and paste the URL into **Start URLs** — every filter (location, salary, industry, seniority) comes along.
5. Set **Max Items** and run. Export as JSON, CSV, Excel, or pull via API.

#### Example input

```json
{
  "searchQueries": ["senior software engineer", "data scientist"],
  "workplaceTypes": ["Remote", "Hybrid"],
  "commitmentTypes": ["Full Time"],
  "maxItems": 1000,
  "maxPagesPerSearch": 15
}
```

Advanced — paste a filtered hiring.cafe URL:

```json
{
  "startUrls": ["https://hiring.cafe/?searchState=%7B%22searchQuery%22%3A%22product%20manager%22%7D"],
  "maxItems": 2000
}
```

***

### 💡 Popular use cases

#### 🎯 Recruiting & sourcing

Build targeted talent-market maps: which companies hire which roles, at what seniority, remote or onsite, with what tools. Track competitors' openings and salary bands over time.

#### 💰 B2B sales & lead generation

Job postings are the strongest buying signal. Filter by **funding stage**, **company size**, **industry** and **technical tools** to find companies that are growing and adopting your category — with a direct link and the hiring source. Separate **direct employers** from agencies instantly.

#### 📊 Labour-market & salary research

Aggregate structured salary, seniority and experience data across categories and regions. Power dashboards, compensation benchmarks and economic research with clean, machine-readable fields.

#### 🌍 Remote-jobs & niche job boards

Feed a remote-only or niche job board with fresh, de-duplicated, richly-tagged listings — including remote-worldwide flags and per-country workplace data.

#### 🤖 AI & data products

Every job ships as structured JSON with 90+ fields — ideal for RAG pipelines, LLM agents, matching engines and analytics without any parsing.

***

### 🎛️ Filters explained

- **Search Queries** — semantic search; natural phrases work (`senior react engineer remote`). Each query is scraped separately.
- **Workplace Type** — Remote, Hybrid and/or Onsite.
- **Commitment Type** — Full Time, Part Time, Contract, Internship, Temporary, Seasonal, Volunteer.
- **Start URLs** — the power-user route: filter on hiring.cafe, copy the URL, and every advanced filter (location, salary, industry, seniority) is applied.
- **Max Items / Max Pages per Search** — control run size. Each page returns roughly 100 jobs.

***

### ❓ FAQ

**Do I need an account or API key?**
No. Just enter a query and run.

**How is this different from other job scrapers?**
The data is AI-structured: 90+ fields per job (salary, seniority, experience, skills, remote type) plus 20+ company fields (funding, size, industry). Ordinary scrapers only give title + company + link.

**Can I use complex filters (location, salary, industry)?**
Yes — apply them on hiring.cafe and paste the URL into **Start URLs**.

**Do all jobs have a salary?**
Only where the employer discloses it. When present, it's returned as structured min/max with a period.

**How many jobs can I get?**
As many as you like. Set **Max Items** to `0` for unlimited, or cap it to control run size.

**What formats can I export?**
JSON, CSV, Excel, HTML table, RSS and via the Apify API. Connect to Make, Zapier, Google Sheets, webhooks or an MCP server.

**Can I run it on a schedule?**
Yes — use Apify **Schedules** to keep your dataset fresh hourly, daily or weekly.

***

### 🔌 Integrations

- Export to **JSON, CSV, Excel, HTML, RSS**.
- Pull data via the **Apify API** or client libraries.
- Connect to **Make, Zapier, Google Sheets, Slack, webhooks** and more.
- Use it from an **MCP server** in your AI agent / LLM workflow.
- Chain it into your own Actors and pipelines.

***

### 📇 Tips for best results

- Use natural, specific queries — semantic search rewards detail (`staff backend engineer fintech remote`).
- For location/salary/industry filters, use **Start URLs** copied from hiring.cafe.
- Start with a small **Max Items** to preview the shape, then scale up.
- Keep the default **Datacenter** proxy — it's fast and low-cost for this site.

***

### ⚖️ Legal & responsible use

This scraper collects **publicly available** job-listing information only — the same postings any visitor can see without logging in. It does not access private data or anything behind authentication.

You are responsible for how you use the collected data. Please:

- Respect Hiring.cafe's Terms of Service and applicable laws (including GDPR/CCPA).
- Use any personal or company data lawfully and for legitimate purposes.
- Scrape responsibly and avoid excessive request rates.

This tool is provided for lawful purposes such as recruiting, market research and business intelligence. It is not affiliated with, endorsed by, or connected to Hiring.cafe.

# Actor input Schema

## `searchQueries` (type: `array`):

What to search for. Hiring.cafe uses semantic search, so natural queries work well: 'software engineer', 'senior product designer remote', 'nurse london'. Each query is scraped separately. Leave empty if you use Start URLs.

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

Optional. Apply any filters on hiring.cafe in your browser, then paste the resulting URL(s) here — the scraper paginates through them. Gives access to every filter (location, salary, seniority, industry, etc.). When provided, the fields below are ignored for these URLs.

## `workplaceTypes` (type: `array`):

Filter by where the job is done. Leave empty for all.

## `commitmentTypes` (type: `array`):

Filter by employment type. Leave empty for all.

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

Maximum number of jobs to collect across all searches. 0 = unlimited.

## `maxPagesPerSearch` (type: `integer`):

How many result pages to scrape per query / URL. Each page returns roughly 100 jobs.

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

Apify Proxy (Datacenter) is enabled by default and works out of the box — keep it. Residential is not recommended and is billed per GB without improving reliability here.

## Actor input object example

```json
{
  "searchQueries": [
    "software engineer"
  ],
  "startUrls": [],
  "workplaceTypes": [],
  "commitmentTypes": [],
  "maxItems": 100,
  "maxPagesPerSearch": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `dataset` (type: `string`):

Open to view, filter and export all scraped jobs from this run (JSON, CSV, Excel).

# 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 = {
    "searchQueries": [
        "software engineer"
    ],
    "startUrls": [],
    "maxItems": 100,
    "maxPagesPerSearch": 5,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("haketa/hiring-cafe-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 = {
    "searchQueries": ["software engineer"],
    "startUrls": [],
    "maxItems": 100,
    "maxPagesPerSearch": 5,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("haketa/hiring-cafe-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 '{
  "searchQueries": [
    "software engineer"
  ],
  "startUrls": [],
  "maxItems": 100,
  "maxPagesPerSearch": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call haketa/hiring-cafe-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,haketa/hiring-cafe-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/kEfV0UuEcOlXzzJYO/builds/VugMxXHDsLoQ9SOFG/openapi.json