# Jobs In New York On The Muse

**Use case:** 

13,916 listings sit under the New York, NY label on The Muse — the densest city on the board. The search is sent to the source as a location query and then checked a second time against each job's own parsed label, so purely remote rows do not drift in.

## Input

```json
{
  "categories": [],
  "levels": [],
  "remoteOnly": false,
  "locations": [
    "New York, NY"
  ],
  "companies": [],
  "keywords": [],
  "excludeKeywords": [],
  "countries": [],
  "locationContains": "New York",
  "categoryContains": [],
  "levelContains": [],
  "companyContains": [],
  "excludeCompanies": [],
  "postedWithinDays": 0,
  "withDescriptionOnly": false,
  "descriptionFormat": "text",
  "compactOutput": false,
  "excludeEmptyFields": false,
  "newestFirst": true,
  "onlyNew": false,
  "emitUnchanged": false,
  "maxItems": 1000
}
```

## Output

```json
{
  "title": {
    "label": "Job title",
    "format": "string"
  },
  "company": {
    "label": "Company",
    "format": "string"
  },
  "location": {
    "label": "Location",
    "format": "string"
  },
  "location_city": {
    "label": "City",
    "format": "string"
  },
  "location_state": {
    "label": "State",
    "format": "string"
  },
  "location_country": {
    "label": "Country",
    "format": "string"
  },
  "is_remote": {
    "label": "Remote",
    "format": "boolean"
  },
  "locations_all": {
    "label": "All locations",
    "format": "array"
  },
  "category": {
    "label": "Category",
    "format": "string"
  },
  "categories_all": {
    "label": "All categories",
    "format": "array"
  },
  "level": {
    "label": "Seniority",
    "format": "string"
  },
  "levels_all": {
    "label": "All levels",
    "format": "array"
  },
  "employment_type": {
    "label": "Employment type",
    "format": "string"
  },
  "tags": {
    "label": "Tags",
    "format": "array"
  },
  "description_text": {
    "label": "Advert text",
    "format": "string"
  },
  "contact_emails": {
    "label": "Emails in advert",
    "format": "array"
  },
  "contact_urls": {
    "label": "Links in advert",
    "format": "array"
  },
  "published_at": {
    "label": "Published",
    "format": "string"
  },
  "posted_days_ago": {
    "label": "Days ago",
    "format": "integer"
  },
  "url": {
    "label": "Listing",
    "format": "string"
  },
  "change_type": {
    "label": "Change",
    "format": "string"
  },
  "job_id": {
    "label": "Job ID",
    "format": "string"
  },
  "scraped_at": {
    "label": "Scraped at",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [The Muse API, Job Board Scraper: Jobs API, Job Search, Postings](https://apify.com/snow_leo_data/the-muse-jobs-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/snow_leo_data/the-muse-jobs-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/snow_leo_data/the-muse-jobs-scraper.md

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`).