LinkedIn Jobs Search Scraper - Public Listings

Search public LinkedIn job listings by keyword and location. Export job title, company, location, canonical listing URL, posting date, LinkedIn job ID and the company's LinkedIn page without login - and, on request, the seniority level, employment type, job function, industries, applicant count, published pay range and full description from each posting. Results are returned as clean, typed dataset rows suitable for CSV, JSON, automation, and AI-agent workflows.

What data can I extract?

Every search result carries title, company, location, url, posted_at, posted_at_timestamp, job_id and company_url. posted_at_timestamp is posted_at parsed into a UTC ISO 8601 timestamp (handles both an absolute source date and a relative age like "3 days ago" or "Just now"); it is null when posted_at is missing or not in a recognized shape.

Set include_details to true and each result also carries seniority_level, employment_type, job_function, industries, applicant_count, salary and job_description, read from the job posting itself. That costs one extra request per job, so those runs take noticeably longer; leave it off for fast, cheap list-only runs.

The dataset schema documents every field before a run starts.

Input example

{
  "search_query": "data engineer",
  "location": "Austin, Texas",
  "max_items": 10,
  "max_pages": 1,
  "include_details": false
}

max_items is a hard output and billing ceiling. Source fields may be null when the upstream public record does not provide them - applicant_count in particular is hidden on some postings, and the six detail fields stay empty unless include_details is true.

Output example

Each dataset item is one normalized result. The field names shown under What data can I extract are emitted as typed JSON properties and can be exported as CSV, Excel, XML, or RSS.

Common use cases

• Lead, market, compliance, and competitive research
• Scheduled monitoring and change detection
• CSV/JSON enrichment pipelines
• AI-agent retrieval and workflow automation

Pricing and cost control

Output is billed per result at $0.001 per result (about $1.00 per 1,000 results), plus a $0.001 Actor-start charge billed once per gigabyte of memory at run start. Use max_items to cap both output volume and charges. The price shown on the Apify Store listing is authoritative.

Use with AI agents and MCP

Apify's MCP server can discover and call this Actor. Example intent:

Find 50 public data-engineer jobs in Austin with company names and listing URLs.

Use the JSON input above as the tool arguments, changing filters and max_items as needed. The strict input schema rejects unknown properties, and the typed dataset schema describes the returned tool data.

Reliability

Runs use bounded retries, deduplication, hard result limits, and explicit failure handling. Browser-based sources are monitored by contract canaries and staged selector repair; official-API sources use deterministic contract canaries rather than DOM repair.

Limitations and responsible use

• Publicly available source data only; coverage and field availability depend on the upstream source.
• A successful search can legitimately return no matching records.
• Point-in-time fields can change after collection.
• Use the data in accordance with applicable law and source terms.
• Do not use results for prohibited eligibility, discrimination, or sensitive-person profiling decisions.

FAQ

What search phrases does this Actor support?

The input schema lists exact accepted fields and examples. Primary discovery terms: LinkedIn jobs scraper, public job listings, job search API, LinkedIn job leads.

Can I control cost?

Yes. Set max_items; it is enforced as the maximum number of output records.

Can an AI agent call it?

Yes. Use Apify MCP search-actors, inspect this Actor's schema, then call it with the same JSON accepted in Console.

Does it require an external API key or login?

No external API key or account login is required. The Actor queries public listings directly.

Changes

See ./CHANGELOG.md for contract and maintenance updates.