LinkedIn Jobs Search Scraper

Extract structured job listings from LinkedIn with keyword search, location targeting, and advanced filters. Collect job titles, descriptions, company information, salary estimates, applicant counts, and direct apply links in JSON, CSV, or Excel format.

Why Choose This Scraper?

• No LinkedIn Account Required: Scrapes public job listings safely without logging in or risking account restrictions.
• Fast and Lightweight: API-powered scraping delivers results in seconds without browser overhead.
• Granular Filtering: Filter by date posted, employment type, seniority level, company ID, remote status, and search radius.
• Complete Job Details: Retrieve full descriptions, salary ranges, company websites, and applicant numbers.
• Flexible Export: Export clean, normalized data directly to JSON, CSV, Excel, or consume via Apify API.

Features

• Keyword and Title Search: Full-text search across job titles, skills, and descriptions.
• Location and Radius Targeting: Search by city, country, or LinkedIn geo ID with kilometer radius support.
• Employment Type Filters: Filter by full-time, part-time, contract, or internship positions.
• Experience and Seniority Levels: Target entry level, associate, mid-senior level, director, or executive roles.
• Remote Work Filter: Quickly isolate remote and work-from-home job opportunities.
• Company-Specific Search: Filter jobs posted by a specific employer using their LinkedIn company ID.
• Freshness and Date Posted: Fetch jobs posted today, in the past 3 days, past week, or past month.
• Sorting Options: Order results by relevance or by date (newest first).
• Direct Apply Links: Access direct application URLs and third-party publisher links.
• Compensation Data: Extract base salary, minimum and maximum ranges, period, and currency when available.
• Applicant Statistics: Track applicant counts to evaluate competition for job openings.

Quick Start

1. Enter your search query (such as "Software Engineer" or "Marketing Manager").
2. Optionally specify a location (such as "New York, NY" or "United Kingdom") or custom filters.
3. Choose the number of pages to collect (each page returns up to 10 listings).
4. Run the actor and download your dataset in CSV, JSON, or Excel format.

Input Parameters

Parameter	Type	Required	Default	Description
query	String	Yes	-	Job search keywords, title, or skills (e.g., "Backend Engineer").
location	String	No	-	Geographic location filter (e.g., "London, UK", "San Francisco, CA").
page	Integer	No	1	Starting page number (range: 1 to 100).
num_pages	Integer	No	1	Number of pages to retrieve (range: 1 to 20, 10 jobs per page).
country	String	No	"us"	Two-letter ISO country code (e.g., "us", "uk", "de", "in") for proxy exit market.
sort_by	String	No	"relevance"	Sort ordering: relevance (default) or date (newest first).
date_posted	String	No	"all"	Posting timeframe: all, today, 3days, week, or month.
employment_types	String	No	-	Filter by employment type: FULLTIME, PARTTIME, CONTRACTOR, INTERN.
seniority_levels	String	No	-	Filter by seniority: Internship, Entry level, Associate, Mid-Senior level, Director, Executive, Not Applicable.
remote_jobs_only	Boolean	No	false	When enabled, returns only listings explicitly marked as remote.
company_id	String	No	-	Restrict results to a specific LinkedIn company by its numeric company ID.
geo_id	String	No	-	LinkedIn numeric geo ID for precise location targeting (e.g., "102571732").
radius	Integer	No	-	Search radius in kilometers around the geo_id location (requires geo_id).
include_details	Boolean	No	true	Fetch extended job details (descriptions, salary, applicant counts). Set to false for faster runs.
fields	String	No	-	Comma-separated list of specific fields to return in the output dataset.

Example Input

{
  "query": "Backend Engineer",
  "location": "San Francisco, CA",
  "num_pages": 2,
  "date_posted": "week",
  "employment_types": "FULLTIME",
  "sort_by": "date",
  "remote_jobs_only": false,
  "include_details": true
}

Output Data Structure

Each dataset item represents one job listing. Output fields are organized into logical categories:

Job Details

Field	Type	Description
job_id	String	LinkedIn job ID
job_title	String	Full title of the job posting
job_description	String	Full job description text
job_employment_type	String	Primary employment type (e.g., Full-time)
job_employment_types	Array	All matching employment types
job_seniority_level	String	Required experience level
job_function	String	Functional department
job_industries	Array	Industry categories associated with the job
job_is_remote	Boolean	Whether the role is marked as remote
job_highlights	Object	Key highlights extracted from the listing

Employer Information

Field	Type	Description
employer_name	String	Company or organization name
employer_logo	String	URL to the company logo image
employer_website	String	Official company website URL
employer_linkedin_url	String	URL to company profile on LinkedIn
job_linkedin_company_id	String	Numeric LinkedIn company ID

Location Details

Field	Type	Description
job_location	String	Location string as listed on LinkedIn
job_city	String	City name
job_state	String	State or region
job_country	String	Country code
job_latitude	Number	Geographic latitude
job_longitude	Number	Geographic longitude

Compensation and Salary

Field	Type	Description
job_salary_string	String	Formatted salary range string
job_min_salary	Number	Minimum compensation figure
job_max_salary	Number	Maximum compensation figure
job_salary_period	String	Salary frequency (e.g., year, hour)
job_salary_currency	String	Currency code (e.g., USD, EUR, GBP)

Application and Metadata

Field	Type	Description
job_apply_link	String	Direct apply URL
job_apply_is_direct	Boolean	Whether the application link is direct
apply_options	Array	Available application methods
job_publisher	String	Publisher or source platform
job_applicants_count	Number	Number of registered applicants
job_posted_at	String	Relative posting time (e.g., "3 days ago")
job_posted_at_date	String	Formatted date of the posting
scraped_at	String	Timestamp when the job was collected

Example Output

{
  "source": "linkedin_jobs_search",
  "search_query": "Backend Engineer",
  "position": 1,
  "job_id": "3849102847",
  "job_title": "Senior Backend Engineer",
  "employer_name": "Stripe",
  "employer_logo": "https://media.licdn.com/dms/image/v2/company-logo/stripe.png",
  "employer_website": "https://stripe.com",
  "employer_linkedin_url": "https://www.linkedin.com/company/stripe",
  "job_location": "San Francisco, CA",
  "job_city": "San Francisco",
  "job_state": "California",
  "job_country": "US",
  "job_is_remote": false,
  "job_employment_type": "Full-time",
  "job_seniority_level": "Mid-Senior level",
  "job_salary_string": "$175,000 - $225,000 / year",
  "job_min_salary": 175000,
  "job_max_salary": 225000,
  "job_salary_currency": "USD",
  "job_salary_period": "year",
  "job_applicants_count": 42,
  "job_posted_at": "3 days ago",
  "job_posted_at_date": "2026-09-22",
  "job_apply_link": "https://www.linkedin.com/jobs/view/3849102847",
  "job_description": "We are looking for a Senior Backend Engineer to join our payments infrastructure team...",
  "scraped_at": "2026-09-25T07:30:00.000Z"
}

Use Cases

• Recruitment and Talent Sourcing: Identify active job openings and monitor demand for specific skills across technology, marketing, and finance sectors.
• Job Market Intelligence: Track job posting volume, skill requirements, and hiring velocity across different regions and industries.
• Competitive Analysis: Monitor hiring patterns, department expansions, and open positions at competitor organizations.
• Salary Benchmarking: Collect advertised compensation data across industries and experience levels to determine competitive salary structures.
• Job Boards and Aggregators: Populate specialized job boards, career discovery platforms, and automated candidate alert feeds.
• Career Research: Evaluate open positions based on remote flexibility, required seniority, and location preferences.

Tips for Best Results

• Optimize Speed: When you only need basic listing data (titles, companies, locations), set include_details to false for up to 3x faster execution.
• Precise Geography: Combine geo_id and radius for accurate regional targeting instead of relying solely on general location strings.
• Target Fresh Roles: Set date_posted to today or week and sort by date to capture recently posted jobs with lower applicant competition.
• Pagination Control: Use num_pages (up to 20 per run) to balance speed and data volume. Each page fetches up to 10 listings.
• Company Intelligence: Use company_id to track all open positions posted by a single organization.

Dataset Views

This actor includes a pre-configured table view in the Apify Console:

• LinkedIn Jobs Overview: Clean, organized table displaying Job Title, Company, Logo, Location, Employment Type, Seniority, Salary, Applicants, Date Posted, and Apply Link.

Limitations

• Each search page contains up to 10 job listings.
• Up to 20 pages (200 jobs) can be retrieved in a single run. For higher volumes, paginate with the page parameter.
• Radius search requires a valid numeric LinkedIn geo_id.
• Salary details are only present when disclosed by the employer in the job posting.

Frequently Asked Questions

Do I need a LinkedIn account or login credentials?

No. The scraper accesses public LinkedIn job search results. You do not need to provide LinkedIn cookies, passwords, or personal account details.

How many jobs can I collect per run?

You can collect up to 200 jobs per run (20 pages with 10 listings each). For larger datasets, schedule recurring runs or paginate through results using the page parameter.

How fast does the scraper execute?

Basic listing queries complete in seconds. When include_details is set to true, the scraper retrieves full job descriptions, salary data, and applicant counts, which adds a short processing time to ensure complete data collection.

Can I filter for remote-only positions?

Yes. Set remote_jobs_only to true to restrict results exclusively to positions marked as remote by the employer.

What export formats are supported?

Data can be exported in JSON, CSV, Excel, XML, or HTML table format directly from the Apify platform or programmatically via the Apify API.

Related Actors

Complement your LinkedIn recruitment and intelligence pipeline with other actors:

• LinkedIn Profile Scraper: Extract complete LinkedIn profile information, including work experience, education, skills, verified professional emails, and company details without logging into an account. Ideal for candidate screening, talent sourcing, and reaching out to hiring managers.

Tags

linkedin jobs scraper linkedin job search scrape linkedin jobs linkedin scraper linkedin api job search api extract linkedin jobs job scraper linkedin employment data remote jobs scraper salary data scraper recruitment intelligence talent sourcing tool job market data linkedin crawler apify linkedin jobs

Get Started

1. Click try for free on this actor page. Sign up using this link
2. Enter your job keywords in the Query field.
3. Configure optional location, date, or seniority filters.
4. Click Start to run the actor and export your structured job data.