Google Jobs Scraper

Give it job searches ("software engineer", "registered nurse") and places ("Seattle, WA", "Berlin"), and it returns one JSON row per Google Jobs result: title, company, location, posted date, salary (as shown and parsed), job type, full description and every apply link Google lists. $8.10 per 1,000 jobs on the Free plan, $3.15 on Business plans and above; you pay only for rows you get.

$8.10 per 1,000 jobs on the Free plan, down to $3.15 on higher plans

Why this actor

• The company's own ATS posting is picked as the best apply link, with the ATS and board detected.
• Goes past Google's 10 jobs per page to 60-150 jobs per search, with Google's own filters.
• SerpApi parameter names (q, date_posted, employment_type, gl, hl, num_pages) and these field names are also accepted: query, location, jobType, maxResults, maxPagesPerQuery, remote.
• No login; recruiter names, emails and phones are never output. Empty searches are free rows.

What you get

Sample row (from the README example; long text shortened, lists cut to two items):

{
  "rowType": "job",
  "platform": "google-jobs",
  "jobId": "d6Zuw_TVelot7iRuAAAAAA==",
  "title": "Software Development Engineer, Network Monitoring and Remediation (NMR)",
  "companyName": "Amazon Web Services, Inc.",
  "location": "Seattle, WA",
  "via": "Indeed",
  "postedAgo": "5 days ago",
  "postedAt": "2026-10-17",
  "salaryText": "$144K–$194K a year",
  "salary": {
    "min": 144000,
    "max": 194000,
    "currency": "USD",
    "period": "year",
    "source": "structured"
  },
  "employmentType": "Full-time",
  "employmentTypes": [
    "FULLTIME"
  ],
  "qualification": null,
  "workFromHome": false,
  "description": "DESCRIPTION\n\nAmazon's network carries traffic for hundreds of millions of customers ...",
  "descriptionComplete": true,
  "applyUrl": "https://www.indeed.com/viewjob?jk=917ad7a1f42a4176&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic",
  "applyOptions": [
    {
      "source": "Indeed",
      "label": "Apply on Indeed",
      "url": "https://www.indeed.com/viewjob?jk=917ad7a1f42a4176&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic",
      "domain": "indeed.com",
      "ats": null
    },
    {
      "source": "LinkedIn",
      "label": "Apply on LinkedIn",
      "url": "https://www.linkedin.com/jobs/view/software-development-engineer-network-monitoring-and-remediation-nmr-at-amazon-web-services-aws-4480587462?utm_campaign=go...",
      "domain": "linkedin.com",
      "ats": null
    }
  ],
  "googleJobsUrl": "https://www.google.com/search?ibp=htl;jobs&q=software+engineer+jobs+in+seattle&htidocid=d6Zuw_TVelot7iRuAAAAAA%3D%3D",
  "searchText": "software engineer in Seattle, WA",
  "query": "software engineer",
  "searchLocation": "Seattle, WA",
  "position": 2,
  "language": "en",
  "country": "US",
  "scrapedAt": "2026-10-22T08:00:00.000Z"
}

Price

Live Apify price on 2026-11-03, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.001 per GB of memory when a run starts.

Use cases

• Job market and salary research: who is hiring for a role, where, at what pay, by job type.
• Recruiting, sourcing and sales: companies hiring for X (a buying signal), with links to their career sites.
• Job boards and aggregators: fresh postings with full text and every apply link, deduplicated by jobId.
• Joining with ATS data: jobsDbExport gives the company's Greenhouse, Lever, Workday ... board and posting id.
• AI agents: "open jobs for X in Y this week" as clean rows.

Run it from code or an AI agent

Actor ID arcadium/google-jobs. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.

curl -X POST "https://api.apify.com/v2/acts/arcadium~google-jobs/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["software engineer"],"locations":["Seattle, WA"],"datePosted":"any","remoteOnly":false,"maxResultsPerQuery":10,"country":"US","language":"en","includeDescription":true}'

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/google-jobs').call({
  "queries": [
    "software engineer"
  ],
  "locations": [
    "Seattle, WA"
  ],
  "datePosted": "any",
  "remoteOnly": false,
  "maxResultsPerQuery": 10,
  "country": "US",
  "language": "en",
  "includeDescription": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/google-jobs").call(run_input={
    "queries": ["software engineer"],
    "locations": ["Seattle, WA"],
    "datePosted": "any",
    "remoteOnly": False,
    "maxResultsPerQuery": 10,
    "country": "US",
    "language": "en",
    "includeDescription": True,
})
items = client.dataset(run.default_dataset_id).list_items().items  # apify-client 3.x returns a Run object
print(items)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/google-jobs",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/google-jobs")
rows = tool.invoke({"run_input": {
    "queries": ["software engineer"],
    "locations": ["Seattle, WA"],
    "datePosted": "any",
    "remoteOnly": False,
    "maxResultsPerQuery": 10,
    "country": "US",
    "language": "en",
    "includeDescription": True,
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/google-jobs",
    run_input={
        "queries": ["software engineer"],
        "locations": ["Seattle, WA"],
        "datePosted": "any",
        "remoteOnly": False,
        "maxResultsPerQuery": 10,
        "country": "US",
        "language": "en",
        "includeDescription": True,
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("description") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)

# pip install crewai crewai-tools langchain-apify   (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool

tool = ApifyActorsTool(actor_name="arcadium/google-jobs")
researcher = Agent(
    role="Research analyst",
    goal="Answer with data collected by the tool",
    backstory="Uses public web data.",
    tools=[tool],
)

{
  "nodes": [
    {
      "name": "Run arcadium/google-jobs",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~google-jobs/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"queries\":[\"software engineer\"],\"locations\":[\"Seattle, WA\"],\"datePosted\":\"any\",\"remoteOnly\":false,\"maxResultsPerQuery\":10,\"country\":\"US\",\"language\":\"en\",\"includeDescription\":true}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
  const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
  const url = 'https://api.apify.com/v2/acts/arcadium~google-jobs/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
  const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
  const rows = JSON.parse(res.getContentText());
  if (!rows.length) return;
  const keys = Object.keys(rows[0]);
  const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
  const sheet = SpreadsheetApp.getActiveSheet();
  sheet.clearContents();
  sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
  sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}

Tutorials

• Google Jobs scraper: export job listings with salary and apply links to CSV

Limitations

• Google shows 10 jobs per search. Past that, coverage comes from Google's own filter variants, so the total per search is what those variants list (typically 60-150 for a broad search), not every job Google has.
• Results, ranking and the location area are Google's. A location is sent the way you would type it ("in Seattle, WA"); a very small place may return jobs from the surrounding area.
• Some markets show only a preview of the description (about 400 characters, descriptionComplete: false); the full text is on the apply links.
• Salaries are what Google shows; many postings have none.
• Labels such as "3 days ago" follow language; postedAt, employmentTypes and salary.period are normalised for en, de, fr, es, it, pt and nl.

FAQ

Why do I get fewer jobs than maxResultsPerQuery? Google had no more for that search: its page and filter variants stopped adding new jobs. Broaden the query or the location, or add more locations.

Why is a search an error row with code no_match? Google Jobs listed nothing for it ("It looks like there aren't any Jobs matches"). Check the spelling or broaden it. It is free.

Can I search any country? Yes: set country (and language for local labels), e.g. "country": "IN" or "country": "DE", "language": "de".

Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.

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