LinkedIn Company Jobs Scraper

Extract structured job listings directly from specific target companies on LinkedIn. Scrape by company vanity slug, company profile URL, or numeric company ID with deep keyword, seniority, location, and date posted filters. Collect job titles, full descriptions, employer details, salary figures, applicant counts, and direct apply links in JSON, CSV, or Excel format.

Why Choose This Scraper?

• No LinkedIn Account Required: Scrapes public LinkedIn job listings safely without logging in, cookies, or risking account bans.
• Flexible Company Targeting: Query companies by name, vanity slug (e.g., google), full LinkedIn URL, or numeric company ID (f_C).
• Batch Multiple Companies: Search up to 10 companies simultaneously in a single execution.
• Fast and Lightweight: Real-time API-powered scraping delivers results in seconds. Toggle include_details: false for up to 3x faster runs.
• Granular Filtering: Filter by role keywords, date posted, employment type, seniority level, remote status, and search radius.
• Complete Job Details: Retrieve full descriptions, salary ranges, benefits, applicant counts, and direct apply URLs.
• Flexible Export: Export clean, normalized data directly to JSON, CSV, Excel, or consume via Apify API and webhooks.

Features

• Company-Specific Targeting: Extract all open positions posted by specific employers using company name, LinkedIn URL, or company ID.
• Multi-Company Batching: Provide comma-separated company names or IDs (up to 10) to monitor multiple target organizations in one run.
• Keyword and Role Filtering: Narrow down company job openings with optional keywords (e.g., "Software Engineer", "Product Manager").
• Location and Radius Targeting: Filter by city, country, or LinkedIn numeric 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.
• 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 disclosed by the employer.
• Applicant Statistics & Badges: Track applicant counts and LinkedIn badges (e.g., "Actively Hiring") to evaluate competition.

Quick Start

1. Enter a Company Name/URL (such as google or https://www.linkedin.com/company/microsoft) or a Company ID (such as 1441).
2. (Optional) Add a Keyword Filter (such as "Backend Engineer") or specify a Location.
3. Choose the number of pages to collect (each page returns up to 10 listings).
4. Run the actor and download your structured dataset in CSV, JSON, or Excel format.

Input Parameters

Parameter	Type	Required	Default	Description
company	String	Conditional*	"google"	LinkedIn company vanity slugs or URLs, comma-separated (up to 10). Example: 'google', 'microsoft'. *Either company or company_id is required.
company_id	String	Conditional*	-	LinkedIn numeric company IDs (f_C), comma-separated (up to 10). Example: '1441'. *Either company or company_id is required.
query	String	No	-	Optional keyword filter applied within company jobs (e.g., "Software Engineer"). Leave empty for all company jobs.
location	String	No	-	Geographic location filter (e.g., "London, UK", "San Francisco, CA"). Leave empty for worldwide.
page	Integer	No	1	Starting page number (range: 1 to 100).
num_pages	Integer	No	1	Number of consecutive pages to fetch (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.
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 ~3x faster runs.
fields	String	No	-	Comma-separated list of specific fields to return in the output dataset.

Example Inputs

1. Basic Company Search

{
  "company": "google",
  "num_pages": 1
}

2. Search by Numeric Company ID

{
  "company_id": "1441",
  "query": "Software Engineer",
  "num_pages": 2
}

3. Advanced Filtered Search

{
  "company": "microsoft",
  "query": "Cloud Architect",
  "location": "Redmond, WA",
  "date_posted": "week",
  "employment_types": "FULLTIME",
  "seniority_levels": "Mid-Senior level",
  "sort_by": "date",
  "remote_jobs_only": false,
  "include_details": true,
  "num_pages": 3
}

4. Batch Multiple Companies

{
  "company": "google,microsoft,apple",
  "query": "Data Scientist",
  "remote_jobs_only": true,
  "date_posted": "month",
  "num_pages": 2
}

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 identifier
job_uid	String	Clean numeric 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	Matching employment type codes (e.g., ["FULLTIME"])
job_seniority_level	String	Required experience level (e.g., Mid-Senior 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
job_benefits	Array	Extracted job benefits and perks

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 (e.g., "$174,000 - $252,000 / year")
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
source	String	Source identifier (linkedin_company_jobs)
company_search	String	Company identifier queried
position	Number	Item order index
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 (e.g., LinkedIn)
job_applicants_count	Number	Number of registered applicants
job_applicants_label	String	Formatted applicant count label
job_linkedin_badges	Array	Badges such as "Actively Hiring"
job_posted_at	String	Relative posting time (e.g., "2 days ago")
job_posted_at_date	String	Formatted date of the posting (YYYY-MM-DD)
scraped_at	String	ISO timestamp when the job was collected

Example Output

{
  "source": "linkedin_company_jobs",
  "company_search": "google",
  "position": 1,
  "job_id": "bGlua2VkaW46NDQ2MDk1MjkwNg",
  "job_uid": "4460952906",
  "job_title": "Senior Software Engineer, Infrastructure, Google Cloud Platforms",
  "job_description": "In most instances, this position requires in-person interviews as part of the hiring process. Google's software engineers develop the next-generation technologies that change how billions of users connect...",
  "job_employment_type": "Full-time",
  "job_employment_types": ["FULLTIME"],
  "job_seniority_level": "Mid-Senior level",
  "job_function": "Information Technology and Engineering",
  "job_industries": ["Information Services and Technology", "Information and Internet"],
  "job_is_remote": false,
  "employer_name": "Google",
  "employer_logo": "https://media.licdn.com/dms/image/v2/D4E0BAQGv3cqOuUMY7g/company-logo_100_100/google_logo.png",
  "employer_website": "https://about.google",
  "employer_linkedin_url": "https://www.linkedin.com/company/google",
  "job_linkedin_company_id": "1441",
  "job_apply_link": "https://www.linkedin.com/jobs/view/4460952906",
  "job_apply_is_direct": false,
  "apply_options": [
    {
      "apply_link": "https://www.linkedin.com/jobs/view/4460952906",
      "is_direct": false,
      "publisher": "LinkedIn"
    }
  ],
  "job_publisher": "LinkedIn",
  "job_location": "Kirkland, WA",
  "job_city": "Kirkland",
  "job_state": "Washington",
  "job_country": "US",
  "job_salary_string": "$174,000 - $252,000 / year",
  "job_min_salary": 174000,
  "job_max_salary": 252000,
  "job_salary_period": "year",
  "job_salary_currency": "USD",
  "job_posted_at": "2 days ago",
  "job_posted_at_date": "2026-09-23",
  "job_applicants_count": 46,
  "job_applicants_label": "46 applicants",
  "job_linkedin_badges": ["Actively Hiring"],
  "scraped_at": "2026-09-25T08:00:00.000Z"
}

Use Cases

• Competitor Hiring Intelligence: Monitor open requisitions, expansion departments, and new tech stack adoptions across direct competitors in real time.
• Account-Based Recruiting (ABR): Track target accounts to source top talent, identify departing skills, and reach out to relevant candidates.
• Sales & Lead Generation: Track company hiring spikes (e.g., massive hiring in Sales or Engineering) as buying intent signals for B2B solutions.
• Job Boards and Aggregators: Automatically curate dedicated career feeds and company microsites with always-fresh job openings.
• Salary & Compensation Benchmarking: Collect compensation ranges published by industry leaders to benchmark company salary brackets.
• Investment & Due Diligence: Gauge company health, growth velocity, and strategic pivots through active job posting volume and role types.

Tips for Best Results

• Find Numeric Company IDs: If you need the exact company_id, use our LinkedIn Jobs Search actor. Each scraped job returns job_linkedin_company_id (e.g., 1441 for Google).
• Optimize Speed: When you only need basic listing data (titles, locations, URLs), set include_details to false for up to ~3x faster execution.
• Batch Multiple Companies: Save time and compute by passing multiple companies separated by commas (e.g., google,microsoft,apple).
• 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.

Dataset Views

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

• LinkedIn Company 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 per run. For higher volumes, paginate with the page parameter.
• You can query up to 10 companies simultaneously per run.
• Salary details are only present when disclosed by the employer in the job posting.
• Radius search requires a valid numeric LinkedIn geo_id.

Frequently Asked Questions

Do I need a LinkedIn account or login credentials?

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

How do I find a company's numeric LinkedIn ID (company_id)?

You can find the numeric company ID using the LinkedIn Jobs Search actor. Run a search for any job from the target employer and look for the job_linkedin_company_id field in the dataset output (e.g., 1441 for Google, 1035 for Microsoft). Alternatively, you can simply use the company vanity name (e.g., google).

Can I search multiple companies at once?

Yes. You can provide up to 10 company names or IDs separated by commas in the company or company_id field (e.g., google,microsoft,apple). The scraper will fetch jobs for each company sequentially.

Can I filter jobs by role/title inside a specific company?

Yes. Use the query parameter (e.g., "Software Engineer", "Product Designer"). The scraper will search only within the specified company's open listings.

How many jobs can I collect per run?

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

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 Jobs Search: Search LinkedIn jobs globally with keyword and location filters, extract job_linkedin_company_id, salary ranges, and applicant statistics.
• LinkedIn Profile Scraper: Extract complete LinkedIn profile information, including work experience, education, skills, verified professional emails, and company details without logging into an account.

Tags

linkedin company jobs linkedin company jobs scraper scrape company jobs linkedin jobs scraper company jobs api linkedin job postings extract company jobs competitor hiring tracking recruitment scraper talent sourcing job scraper linkedin api remote jobs scraper apify linkedin job openings scraper company career scraper

Get Started

1. Click Try for free on this actor page. Sign up using this link
2. Enter your target company name or slug in the Company Name or URL field (e.g., google).
3. Configure optional keyword, location, date, or seniority filters.
4. Click Start to run the actor and export your structured job data.