# The Muse Jobs Scraper - Postings, Companies & Locations (`scrapers_lat/themuse-jobs-scraper`) Actor
Scrape The Muse job postings with title, company name and id, locations, category, experience level, remote flag, publication date, apply URL and full description. Filter by category, company, location and level. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/themuse-jobs-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Jobs, Business, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $6.80 / 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/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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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
## The Muse Jobs Scraper - Postings, Companies & Locations
> Collect job postings from The Muse with title, company, locations, category, experience level, remote flag, publication date, apply URL and full description. Filter by category, company, location and level, then export clean structured data for hiring, market research and job aggregation.
**๐ฅ [Input](https://apify.com/scrapers_lat/themuse-jobs-scraper/input-schema) ยท ๐ค [Output](https://apify.com/scrapers_lat/themuse-jobs-scraper/output-schema) ยท ๐ฐ [Pricing](https://apify.com/scrapers_lat/themuse-jobs-scraper/pricing) ยท โถ๏ธ [Examples](https://apify.com/scrapers_lat/themuse-jobs-scraper/examples)**
Full postings title, company & description
Filter by category, level & location
JSON / CSV / Excel output formats
### Who is it for
| Use case | Who benefits |
|---|---|
| Recruiting | Recruiters sourcing openings by role, level and location |
| Job boards | Aggregators keeping fresh, structured listings |
| Market research | Analysts tracking hiring trends by company and category |
| Lead generation | Agencies spotting companies that are actively hiring |
### How to use it
1. Add one or more **Job Categories** (for example Software Engineering, Data Science, Marketing).
2. Optionally narrow by **Company Names**, **Locations** or **Experience Levels**, or add a **Keyword Filter**.
3. Set **Max Jobs To Scrape** and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**How do I get only remote jobs?**
Add `Flexible / Remote` to the Locations field, or filter the output on the `remote` flag, which is true for every remote or flexible role.
**Can I pull jobs from a single company?**
Yes. Add the company profile short name (for example `uber`) to the Company Names field to keep only that company's openings.
**How do I focus on senior roles?**
Add one or more values to Experience Levels, such as `Senior Level` or `Management`.
**How fresh is the data?**
Every posting is read live at run time, so each record reflects what was listed at the moment of the run (see observedAt).
### Related scrapers
- [Greenhouse Jobs Scraper](https://apify.com/scrapers_lat/greenhouse-jobs-scraper)
- [Lever Jobs Scraper](https://apify.com/scrapers_lat/lever-jobs-scraper)
- [Indeed Jobs Scraper](https://apify.com/scrapers_lat/indeed-jobs-scraper)
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with The Muse. It only accesses publicly available job data. Use the results in accordance with the source's terms.
# Actor input Schema
## `categories` (type: `array`):
Filter jobs by category, for example 'Software Engineering', 'Data Science', 'Marketing', 'Sales'. Add one or more. Leave empty to search all categories.
## `companyNames` (type: `array`):
Optional. Restrict to one or more companies by their profile short name on The Muse (for example 'uber', 'bankofamerica').
## `locations` (type: `array`):
Optional. Filter by location, for example 'New York, NY', 'London, England', or 'Flexible / Remote' for remote roles.
## `levels` (type: `array`):
Optional. Filter by experience level, for example 'Entry Level', 'Mid Level', 'Senior Level', 'Management'.
## `keyword` (type: `string`):
Optional. Keep only jobs whose title, company or description contains this text (for example 'python', 'nurse', 'remote').
## `maxJobs` (type: `integer`):
Maximum number of job postings to collect. Optional.
## Actor input object example
```json
{
"categories": [
"Software Engineering"
],
"maxJobs": 50
}
````
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"categories": [
"Software Engineering"
],
"maxJobs": 50
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/themuse-jobs-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 = {
"categories": ["Software Engineering"],
"maxJobs": 50,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/themuse-jobs-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"categories": [
"Software Engineering"
],
"maxJobs": 50
}' |
apify call scrapers_lat/themuse-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/themuse-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "The Muse Jobs Scraper - Postings, Companies & Locations",
"description": "Scrape The Muse job postings with title, company name and id, locations, category, experience level, remote flag, publication date, apply URL and full description. Filter by category, company, location and level. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "0MhqAjHthOddpRbC8"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~themuse-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-themuse-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~themuse-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-themuse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~themuse-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-themuse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"categories": {
"title": "Job Categories",
"type": "array",
"description": "Filter jobs by category, for example 'Software Engineering', 'Data Science', 'Marketing', 'Sales'. Add one or more. Leave empty to search all categories.",
"items": {
"type": "string"
}
},
"companyNames": {
"title": "Company Names",
"type": "array",
"description": "Optional. Restrict to one or more companies by their profile short name on The Muse (for example 'uber', 'bankofamerica').",
"items": {
"type": "string"
}
},
"locations": {
"title": "Locations",
"type": "array",
"description": "Optional. Filter by location, for example 'New York, NY', 'London, England', or 'Flexible / Remote' for remote roles.",
"items": {
"type": "string"
}
},
"levels": {
"title": "Experience Levels",
"type": "array",
"description": "Optional. Filter by experience level, for example 'Entry Level', 'Mid Level', 'Senior Level', 'Management'.",
"items": {
"type": "string"
}
},
"keyword": {
"title": "Keyword Filter",
"type": "string",
"description": "Optional. Keep only jobs whose title, company or description contains this text (for example 'python', 'nurse', 'remote')."
},
"maxJobs": {
"title": "Max Jobs To Scrape",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of job postings to collect. 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
}
}
}
}
}
}
}
}
}
}
```