LinkedIn Jobs by Location

Compare the same LinkedIn job search across up to 20 cities, regions, or countries in one run. Each row keeps the requested search location, so teams can group jobs by market without managing separate exports. No LinkedIn account, cookies, or proxy setup is required.

The current Store configuration charges $0.005 at run start and $0.002 per accepted job row. Apify platform usage is billed separately to the user.

A location matrix for hiring demand

This Actor is designed for a repeated location question: where is a specific role currently being advertised? Workforce planners can compare target hiring markets with one consistent keyword. Staffing teams can build regional sourcing queues that retain the exact city, region, or country used for each search.

Each location is paginated and reported separately. A source failure for one location allows later locations to be attempted. Global item, page, and billing limits stop remaining work, and OUTPUT_SUMMARY identifies skipped locations.

Sample output

{
  "jobId": "4001000002",
  "title": "DevOps Engineer",
  "company": "Berlin Tech GmbH",
  "location": "Berlin, Germany",
  "salary": "€70,000/yr - €90,000/yr",
  "postedAt": "2026-07-19",
  "postedText": "1 day ago",
  "url": "https://www.linkedin.com/jobs/view/4001000002/",
  "searchKeywords": "DevOps engineer",
  "searchLocation": "Berlin, Germany",
  "scrapedAt": "2026-07-20T09:00:00.000Z"
}

location is the text shown on the posting. searchLocation is the market requested in the input. A remote role or regional posting can make those values different, which is useful when the output is grouped later.

Input

Add one to 20 entries in locations, using the place names you would enter in LinkedIn search. The optional keywords value is applied to each location.

{
  "locations": [
    "Berlin, Germany",
    "Munich, Germany",
    "Hamburg, Germany",
    "Frankfurt, Germany"
  ],
  "keywords": "DevOps engineer",
  "maxItemsPerLocation": 100,
  "maxTotalItems": 1000,
  "maxTotalPages": 120
}

maxItemsPerLocation is a safety cap, up to 1,000 jobs. Reaching it marks that location incomplete in OUTPUT_SUMMARY. The full run is bounded to 10,000 returned rows and 400 result-page requests.

Output stays at the job-card level. For supported filters, bulk keyword-location combinations, and bounded public detail enrichment, use linkedin-jobs-scraper.

Output and export

Rows contain job ID, title, company, posting location, salary when shown, posting date, URL, requested location, keyword, and fetch time. Export the dataset as JSON, CSV, Excel, or XML, or retrieve it through the Apify dataset API.

The summary records counts and stop reasons for each location, skipped locations, total budgets, and overall completeness. A source block, parser failure, transport failure, configured cap, or billing limit is reported as an incomplete result.

Pricing

The current public configuration uses a $0.005 Actor-start event and a $0.002 job-collected event. A run returning 800 accepted rows creates $1.605 in Actor event charges. Apify platform usage, including compute and data transfer where applicable, is charged separately under the user's Apify plan.

An empty location has no per-job event. The start event and any platform usage can still apply.

Choosing the right LinkedIn Jobs Actor

Use this Actor when one keyword must be compared across named markets with a separate result group for each. Use linkedin-jobs-scraper when the work needs supported filters, different keywords per query, optional company or geo IDs, or available public detail fields.

Common questions

Can one run mix countries and cities? Yes. Each location is processed as its own search segment.

Why does a location show zero jobs? Check its stop reason in OUTPUT_SUMMARY. A genuine empty final page is distinguished from a blocked or unparsable response.

Does salary appear on each row? Salary is null when LinkedIn omits it from the public card.

How do I know the comparison is complete? Confirm the run-level complete value and review each location entry before using the counts in a market comparison.

Support

Include the Apify run ID, input locations, keyword, and OUTPUT_SUMMARY when reporting a reproducible issue. Remove private labels or downstream customer data first.