# Google Jobs Scraper — Listings, Salary, Filters (`scrape.badger/google-jobs-scraper`) Actor
Scrape Google Jobs at scale: structured job listings with title, company, location, salary, posted date, job type, schedule, apply links, qualifications and responsibilities. Two data sources — Google Careers RPC (fast, ~1-2s) for Google's own openings.
- **URL**: https://apify.com/scrape.badger/google-jobs-scraper.md
- **Developed by:** [Scrape Badger](https://apify.com/scrape.badger) (community)
- **Categories:** Jobs, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $8.00 / 1,000 job pages
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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
### What does Google Jobs Scraper do?
Scrape [Google for Jobs](https://www.google.com/search?q=jobs) — the aggregator that pulls from LinkedIn, Indeed, company career pages and more. Keyword + location search with date-posted, job-type, remote, and radius filters.
### Why use Google Jobs Scraper?
- **Aggregated source.** LinkedIn, Indeed, Glassdoor, Monster, company careers — Google de-duplicates across them.
- **Filter set.** `date_posted`, `job_type`, `ltype` (remote), `lrad` (radius).
- **200+ country domains.** Local job markets with `gl` + `hl`.
- **Per-job apply link.** Direct-to-apply URL when Google surfaces it.
- **Two modes.** `rpc` (fast API) or `serp` (full SERP context).
### What data can Google Jobs Scraper extract?
| Field | Type | Description |
|---|---|---|
| title | string | Job title |
| company | string | Employer name |
| location | string | Job location |
| via | string | Source site |
| description | string | Full job description |
| posted_at | string | Human-readable (e.g. '3 days ago') or ISO |
| schedule | string | Full-time / part-time / contract / internship |
| job_type | string | Remote / hybrid / on-site |
| thumbnail | string | Company logo URL |
| apply_link | string | Direct apply URL |
### How to scrape Google Jobs (Google for Jobs)
1. Click **Try for free**.
2. Enter your query in `q` (e.g. `senior backend engineer python`).
3. Optional: set `location`, `date_posted` (past day/week/month), `job_type`, `ltype` (remote only).
4. Set `gl` / `hl` for country + language.
5. Set `max_pages` — each page is ≈ 10 jobs.
6. Click **Start** — jobs stream into the dataset.
### How much will it cost?
**$0.008 per page (≈ $8 per 1,000 pages).** One call per page. A 3-page run pushes ≈ 30 jobs for $0.024.
#### Competitor benchmark
| Actor | Author | Price | Notes |
|---|---|---|---|
| bebity/indeed-scraper | bebity | $29 /mo subscription | Indeed-only |
| curious_coder/linkedin-jobs-scraper | curious_coder | ~$12 / 1k | LinkedIn-only |
| community/google-jobs-scraper | community | ~$10 / 1k | Google-aggregated |
| **scrape-badger/google-jobs-scraper** | **ScrapeBadger** | **$8 / 1k pages** | **20% below closest competitor** |
### Input
Configure the run in the **Input** tab above, or pass a JSON object matching the fields below when calling the Actor via the Apify API.
| Field | Required | Description |
|---|---|---|
| q | ✅ | Job search query. |
| mode | — | `rpc` (default, fast) or `serp` (rich SERP context). |
| location | — | City / region string. |
| date_posted | — | Google enum: `today` / `3days` / `week` / `month`. |
| job_type | — | Full-time / part-time / contract / internship. |
| ltype | — | Remote filter. |
| lrad | — | Radius in km / miles. |
| gl / hl | — | Country + language. |
| max_pages | — | Pagination budget. |
### Output
Every successful run streams records into the run's dataset. Download as JSON, CSV, XML, Excel, or HTML from the **Dataset** tab; consume programmatically via the Apify API or webhooks.
Example record:
```json
{
"title": "Senior Backend Engineer (Python)",
"company": "Acme Corp",
"location": "New York, NY (Remote)",
"via": "LinkedIn",
"description": "We're looking for\u2026",
"posted_at": "3 days ago",
"schedule": "Full-time",
"job_type": "Remote",
"thumbnail": "https://\u2026",
"apply_link": "https://linkedin.com/jobs/view/\u2026"
}
````
### Tips / Advanced options
- **Use `date_posted: today` for real-time sourcing.** Recruiters win by speed — hit Google Jobs with a cron every hour for fresh postings.
- **SERP mode adds context.** `mode: serp` returns richer results (featured snippets, related searches). Slower but better for market intelligence.
- **Dedupe by `apply_link`.** Google aggregates from multiple sources — same job may appear under different `via`. `apply_link` is the canonical dedupe key.
- **`ltype` filters remote-only.** Essential for distributed-team recruiters.
### FAQ, Disclaimers, Support
#### Can I filter by salary?
Not at the query level — Google doesn't consistently surface salary. Post-filter on `description` if the posting includes it.
#### Why are some jobs missing `apply_link`?
Google doesn't always expose it. When absent, the full description typically includes contact info.
#### What's the difference between `mode: rpc` and `mode: serp`?
`rpc` is Google's internal API (fast, cheap, jobs-only). `serp` is the full SERP rendering (more context, slower). Default `rpc` is what most users want.
#### Can I scrape LinkedIn directly?
This actor proxies Google's LinkedIn aggregation. For direct LinkedIn scraping, use a dedicated LinkedIn actor (outside this suite).
#### Disclaimer
This Actor scrapes public Google data only. You're responsible for compliance with Google's Terms of Service and any applicable data-protection laws (GDPR, CCPA, etc.) in your jurisdiction. ScrapeBadger does not store the scraped results — they are delivered directly to your Apify dataset.
#### Support
Something not working? Open a ticket in the **Issues** tab above — we triage within one business day. Full API reference: [docs.scrapebadger.com](https://docs.scrapebadger.com).
#### Powered by
[ScrapeBadger](https://scrapebadger.com) — Google-optimised residential proxy pool + browser-farm fallback, 99.7% uptime, unmetered bandwidth. No CAPTCHAs reach you.
# Actor input Schema
## `q` (type: `string`):
Job title or keywords. Example: software engineer, senior react developer, data scientist remote.
## `mode` (type: `string`):
rpc (default, ~1-2s): Google Careers' own batchexecute RPC — structured JSON with rich fields (qualifications, responsibilities, apply URL). Scope: Google's own openings (~3-4k roles). serp: public Google Jobs vertical (aggregates LinkedIn / Indeed / Built In / ZipRecruiter). Slower; supports the full filter set (job\_type, date\_posted, ltype, radius).
## `gl` (type: `string`):
ISO 3166-1 alpha-2 country code (lowercase). Example: us, gb, de.
## `country` (type: `string`):
Alias for gl. Optional — use this or gl, not both.
## `hl` (type: `string`):
ISO 639-1 language code. Example: en, es, de.
## `language` (type: `string`):
Alias for hl. Accepts locale form like en-US, pt-BR. Optional.
## `domain` (type: `string`):
Google domain to hit. Example: google.com, google.co.uk, google.de.
## `location` (type: `string`):
City / state / region for geo-targeting. Example: New York, NY, London. SERP mode only.
## `job_type` (type: `string`):
Employment type filter. SERP mode only.
## `date_posted` (type: `string`):
Restrict to postings within this window. SERP mode only.
## `ltype` (type: `string`):
Remote / hybrid / onsite filter. SERP mode only.
## `lrad` (type: `string`):
Radius in miles around location. Example: 25. SERP mode only.
## `chips` (type: `string`):
Raw Google chip filter string. Example: date\_posted:today. Optional — overrides the structured fields above when set.
## `uds` (type: `string`):
Opaque UDS filter token copied from a Google Jobs URL. Optional.
## `uule` (type: `string`):
UULE-encoded location string for precise geo targeting. Optional.
## `max_pages` (type: `integer`):
How many pages of jobs to fetch. Each page is a separate API call (costs N credits) and is walked via Google's next\_page\_token. Stops early if Google signals no more pages.
## `next_page_token` (type: `string`):
Resume from a specific page by passing the next\_page\_token returned by a prior run. Optional.
## Actor input object example
```json
{
"q": "software engineer",
"mode": "rpc",
"gl": "us",
"hl": "en",
"domain": "google.com",
"job_type": "",
"date_posted": "",
"ltype": "",
"max_pages": 1
}
```
# Actor output Schema
## `dataset` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"q": "software engineer"
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrape.badger/google-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "q": "software engineer" }
# Run the Actor and wait for it to finish
run = client.actor("scrape.badger/google-jobs-scraper").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 '{
"q": "software engineer"
}' |
apify call scrape.badger/google-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrape.badger/google-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Google Jobs Scraper — Listings, Salary, Filters",
"description": "Scrape Google Jobs at scale: structured job listings with title, company, location, salary, posted date, job type, schedule, apply links, qualifications and responsibilities. Two data sources — Google Careers RPC (fast, ~1-2s) for Google's own openings.",
"version": "1.0",
"x-build-id": "sQWivwNZX6bzxfE17"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrape.badger~google-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrape.badger-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrape.badger~google-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-scrape.badger-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrape.badger~google-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrape.badger-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"q"
],
"properties": {
"q": {
"title": "Job search query",
"type": "string",
"description": "Job title or keywords. Example: software engineer, senior react developer, data scientist remote."
},
"mode": {
"title": "Data source",
"enum": [
"rpc",
"serp"
],
"type": "string",
"description": "rpc (default, ~1-2s): Google Careers' own batchexecute RPC — structured JSON with rich fields (qualifications, responsibilities, apply URL). Scope: Google's own openings (~3-4k roles). serp: public Google Jobs vertical (aggregates LinkedIn / Indeed / Built In / ZipRecruiter). Slower; supports the full filter set (job_type, date_posted, ltype, radius).",
"default": "rpc"
},
"gl": {
"title": "Country",
"type": "string",
"description": "ISO 3166-1 alpha-2 country code (lowercase). Example: us, gb, de.",
"default": "us"
},
"country": {
"title": "Country (alias)",
"type": "string",
"description": "Alias for gl. Optional — use this or gl, not both."
},
"hl": {
"title": "Language",
"type": "string",
"description": "ISO 639-1 language code. Example: en, es, de.",
"default": "en"
},
"language": {
"title": "Language (alias, locale form)",
"type": "string",
"description": "Alias for hl. Accepts locale form like en-US, pt-BR. Optional."
},
"domain": {
"title": "Google domain",
"type": "string",
"description": "Google domain to hit. Example: google.com, google.co.uk, google.de.",
"default": "google.com"
},
"location": {
"title": "City / state / region",
"type": "string",
"description": "City / state / region for geo-targeting. Example: New York, NY, London. SERP mode only."
},
"job_type": {
"title": "Job type",
"enum": [
"",
"FULLTIME",
"PARTTIME",
"CONTRACTOR",
"INTERN"
],
"type": "string",
"description": "Employment type filter. SERP mode only.",
"default": ""
},
"date_posted": {
"title": "Date posted",
"enum": [
"",
"today",
"3days",
"week",
"month"
],
"type": "string",
"description": "Restrict to postings within this window. SERP mode only.",
"default": ""
},
"ltype": {
"title": "Work arrangement",
"enum": [
"",
"remote",
"hybrid",
"onsite",
"work_from_home"
],
"type": "string",
"description": "Remote / hybrid / onsite filter. SERP mode only.",
"default": ""
},
"lrad": {
"title": "Search radius (miles)",
"type": "string",
"description": "Radius in miles around location. Example: 25. SERP mode only."
},
"chips": {
"title": "Chip filter string",
"type": "string",
"description": "Raw Google chip filter string. Example: date_posted:today. Optional — overrides the structured fields above when set."
},
"uds": {
"title": "UDS filter token",
"type": "string",
"description": "Opaque UDS filter token copied from a Google Jobs URL. Optional."
},
"uule": {
"title": "UULE-encoded location",
"type": "string",
"description": "UULE-encoded location string for precise geo targeting. Optional."
},
"max_pages": {
"title": "Max pages",
"minimum": 1,
"maximum": 20,
"type": "integer",
"description": "How many pages of jobs to fetch. Each page is a separate API call (costs N credits) and is walked via Google's next_page_token. Stops early if Google signals no more pages.",
"default": 1
},
"next_page_token": {
"title": "Start page token",
"type": "string",
"description": "Resume from a specific page by passing the next_page_token returned by a prior run. Optional."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```