LinkedIn Job Search
Pricing
Pay per event
LinkedIn Job Search
Extract LinkedIn job listings with salaries, skills, company data & growth insights. Access the world's largest professional network. 200+ countries, structured JSON output, no-code setup.
Pricing
Pay per event
Rating
5.0
(1)
Developer

CheapGET
Actor stats
2
Bookmarked
98
Total users
6
Monthly active users
4 hours ago
Last modified
Categories
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Extract comprehensive LinkedIn job listings with 35+ rich data points per posting.
Unlock professional job intelligence: company ratings, employee counts, salary transparency, and verified employer data. Get detailed job descriptions, skill requirements, remote work options, and hiring team insights—all from the world's largest professional network with 1 billion+ members.
🤝 Support & Community
📧 Support: Contact Us 💬 Community: Telegram Group
🏆 Key Features
💼 Professional Job Intelligence
- 👥 Applicant Insights: Track real-time competition levels—identify high-demand roles vs. hidden opportunities with fewer applicants.
- 📊 Company Verification: Access verified company profiles with employee counts, growth trends, and industry classifications unique to LinkedIn.
- 💰 Salary Transparency: Extract disclosed salary ranges with currency and payment period details from employer postings.
- 🎯 Skills Taxonomy: Capture structured skill requirements aligned with LinkedIn's professional skills graph for precise job-candidate matching.
📈 Comprehensive Job Data
- 🏢 Rich Company Profiles: Company ratings, review counts, revenue ranges, headquarters locations, and official websites.
- 📍 Location Intelligence: Precise job locations with remote/hybrid/on-site work arrangement detection across 200+ countries.
- ⏰ Posting Freshness: Filter by posting date with flexible time ranges (24 hours to custom dates) for time-sensitive recruiting.
- 🔗 Direct Application Links: Both LinkedIn job URLs and direct company career page links for streamlined candidate pipelines.
🎨 Structured Output Format
- 📋 Normalized Schema: Consistent 35+ field structure across all job postings for easy integration and analysis.
- 🗓️ ISO Timestamps: Standardized date formats for posting dates and processing timestamps.
- 📝 Markdown Descriptions: Clean, formatted job descriptions ready for display or further processing.
- 🔢 Quantified Metrics: Numeric fields for salary ranges, vacancy counts, experience requirements, and company ratings.
💰 Pricing
| Resource | Cost | Description |
|---|---|---|
| Actor Usage | $0.00001 | Charged for Actor runtime, proxy and storage. Cost depends on resource consumption during execution |
| Job Details | $0.00252 | Charged for each job posting extracted. Includes complete metadata with salary, skills, and company |
Example Cost Calculation:
- Searching 2 keywords with 100 results each
- Cost: (200 jobs × $0.00252) = $0.504 + runtime fees
🌟 Why choose this Actor?
Built for recruiters, HR tech platforms, and labor market analysts, this Actor transforms LinkedIn's professional job ecosystem into actionable, structured data.
| Feature | LinkedIn Job Search | Bright Data | Octoparse | ScraperAPI |
|---|---|---|---|---|
| Pricing Model | ✅ Pay per use | ❌ Enterprise | ⚠️ Subscription | ⚠️ Credit-based |
| Data Depth | ✅ 35+ fields | ⚠️ 20-25 fields | ⚠️ 15-20 fields | ⚠️ Basic only |
| Company Data | ✅ Verified info | ⚠️ Limited | ⚠️ Basic only | ❌ Not available |
| Salary Data | ✅ Included | ⚠️ Partial | ❌ Not available | ❌ Not available |
| Setup Time | ✅ Instant | ❌ Complex setup | ⚠️ Template req. | ⚠️ API setup |
| Min. Cost | ✅ $0.03 | ❌ $500+/month | ⚠️ $75/month | ⚠️ $49/month |
💻 Input Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
search_terms | string[] | ✅ Yes | Job titles, skills, or company names to search. Each term creates a separate search query. Examples: "Product Manager", "Python Developer", "Google" |
country | string | ✅ Yes | Target country for job search from 95+ supported countries. Must match exact country name (e.g., "United States", not "USA") |
location | string | ❌ No | Optional city, metro area, or region to narrow search results. Examples: "San Francisco Bay Area", "New York City", "London". Leave empty for country-wide search |
distance | integer | ❌ No | Search radius in miles around the specified location. Default: 50 miles. Only applicable when location is provided |
posted_since | string | ✅ Yes | Filter jobs by posting date. Supports relative formats ("1 week", "30 days", "2 months") or absolute dates ("2024-12-01"). Flexible time range filtering |
max_results | integer | ✅ Yes | Maximum number of job listings to extract per search term. Minimum value: 10. Higher values increase runtime and cost proportionally |
📝 Example Input
{"search_terms": ["Product Manager", "Software Engineer"],"country": "United States","location": "San Francisco Bay Area","distance": 25,"posted_since": "1 week","max_results": 100}
📤 Output Structure
| Field | Type | Description |
|---|---|---|
processor | string | URL of the Apify actor that processed this data |
processed_at | string | ISO 8601 timestamp when the data was scraped (format: YYYY-MM-DDTHH:MM:SS+00:00) |
platform | string | Source platform name (LinkedIn) |
platform_url | string | Direct LinkedIn job posting URL |
official_url | string | Company's official career page URL for this job (if available) |
title | string | Job position title as posted by employer |
posted_date | string | ISO 8601 timestamp when the job was originally posted |
location | string | Job location (city, metro area, or "Remote") |
is_remote | boolean | Whether the job allows remote work |
description | string | Full job description in markdown format with responsibilities and requirements |
job_type | string | Employment type (full-time, part-time, contract, temporary, internship) |
job_level | string | Seniority level (entry, associate, mid-senior, director, executive) |
job_function | string | LinkedIn job function category (e.g., Engineering, Marketing, Sales) |
listing_type | string | Listing visibility type (standard, promoted, featured) |
emails | array | Contact email addresses found in job posting (if any) |
phones | array | Contact phone numbers found in job posting (if any) |
social_links | object | Social media profile links for the hiring company |
skills | string | Required skills and technologies extracted from LinkedIn's skill tags |
work_from_home | string | Work arrangement (remote, hybrid, on-site) |
vacancy_count | integer | Number of open positions for this role |
experience_range | string | Required years of experience (e.g., "3-5 years", "5+ years") |
salary_period | string | Payment frequency (yearly, monthly, hourly) |
salary_minimum | number | Minimum salary amount in specified currency |
salary_maximum | number | Maximum salary amount in specified currency |
salary_currency | string | Currency code (USD, EUR, GBP, etc.) |
company_name | string | Verified company name from LinkedIn company page |
company_industry | string | LinkedIn industry classification (e.g., "Technology, Information and Internet") |
company_url | string | LinkedIn company profile page URL |
company_website | string | Official company website URL |
company_logo | string | Company logo image URL from LinkedIn CDN |
company_addresses | string | Company headquarters and office locations |
company_revenue | string | Annual revenue range (e.g., "$100M-$500M", "$1B+") |
company_description | string | Company "About" section from LinkedIn profile |
company_rating | number | Company rating score out of 5.0 based on employee reviews |
employee_count | string | LinkedIn employee count range (e.g., "1001-5000", "10001+") |
review_count | integer | Total number of company reviews on LinkedIn |
📤 Example Output
{"processor": "https://apify.com/cheapget/linkedin-job-search?fpr=aiagentapi","processed_at": "2025-12-30T14:30:00+00:00","platform": "LinkedIn","platform_url": "https://www.linkedin.com/jobs/view/3847291056","official_url": "https://careers.google.com/jobs/results/senior-product-manager","title": "Senior Product Manager, Cloud AI","posted_date": "2025-12-22T00:00:00+00:00","location": "Mountain View, CA","is_remote": false,"description": "Join Google Cloud's AI team to shape the future of enterprise AI products!\n\n## What you'll do\n- Define product roadmap for Cloud AI services\n- Partner with engineering to deliver world-class ML infrastructure\n- Drive go-to-market strategy with cross-functional teams\n- Analyze market trends and competitive landscape","job_type": "full-time","job_level": "senior","job_function": "Product Management","listing_type": "promoted","emails": ["jobs@google.com"],"phones": ["+1-650-253-0000"],"social_links": {"linkedin": "https://www.linkedin.com/company/google","twitter": "https://twitter.com/google","facebook": "https://www.facebook.com/Google"},"skills": "Product Strategy, Machine Learning, Cloud Computing, Agile, SQL, Stakeholder Management","work_from_home": "hybrid","vacancy_count": 3,"experience_range": "5-8 years","salary_period": "yearly","salary_minimum": 180000,"salary_maximum": 260000,"salary_currency": "USD","company_name": "Google","company_industry": "Technology, Information and Internet","company_url": "https://www.linkedin.com/company/google","company_website": "https://google.com","company_logo": "https://media.licdn.com/dms/image/C4D0BAQHiNSL4Or29cg/company-logo_200_200/google-logo.png","company_addresses": "1600 Amphitheatre Parkway, Mountain View, CA 94043","company_revenue": "$280B+","company_description": "A technology company that specializes in Internet-related services and products, including online advertising, search engine, cloud computing, and AI.","company_rating": 4.4,"employee_count": "100001+","review_count": 45000}
🔌 Integrations
Seamlessly connect this actor to your existing pipelines via the Apify API.
Ⓜ️ Make.com Integration
Get Started with Make.com (1000 Free Credits) 🎁
┌────────────────────────────────────────────┐│ Step 1: Configure Actor Module ││ ├─ Add Module: "Run an Actor" ││ ├─ Enable Map: Toggle ON ││ ├─ Actor ID: E4AxzjmyF6mhrmww2 ││ ├─ Refresh: Click Refresh button ││ └─ Input JSON: Add job search parameters │└────────────────────────────────────────────┘↓┌────────────────────────────────────────────┐│ Step 2: Set Execution Mode ││ └─ Run synchronously: YES │└────────────────────────────────────────────┘↓┌────────────────────────────────────────────┐│ Step 3: Retrieve Results ││ ├─ Add Module: "Get Dataset Items" ││ └─ Dataset ID: defaultDatasetId │└────────────────────────────────────────────┘
🎱 N8N.io Integration
Open Source Workflow Automation ⚡
┌────────────────────────────────────────────┐│ Step 1: Add Apify Node ││ ├─ Search: "Run an Actor and get dataset" ││ └─ Category: Apify │└────────────────────────────────────────────┘↓┌────────────────────────────────────────────┐│ Step 2: Configure Actor ││ ├─ Selection Mode: By ID ││ ├─ Actor ID: E4AxzjmyF6mhrmww2 ││ └─ Paste from Actor ID section above │└────────────────────────────────────────────┘↓┌────────────────────────────────────────────┐│ Step 3: Set Input Parameters ││ └─ Modify Input JSON with search terms │└────────────────────────────────────────────┘
📚 API Documentation
- MCP API - Model Context Protocol integration
- Python API - Complete Python client documentation with examples
- JavaScript API - Node.js and browser integration guide
🏗️ Metadata for Developers (JSON-LD)
{"@context": "https://schema.org","@type": "SoftwareApplication","name": "LinkedIn Job Search - Professional Job Data Extraction","alternateName": ["LinkedIn Job Scraper","LinkedIn Job Data Extractor","LinkedIn Recruiting Tool","LinkedIn Job API"],"applicationCategory": "DeveloperApplication","applicationSubCategory": "Professional Job Data Extraction","operatingSystem": "Cloud","offers": {"@type": "Offer","price": "0.00","priceCurrency": "USD","priceValidUntil": "2099-12-31","availability": "https://schema.org/InStock"},"description": "Extract comprehensive LinkedIn job listings with 35+ fields per posting. Includes salary data, company verification, skills taxonomy, and remote work detection. Perfect for recruiters, HR tech platforms, and labor market analysts.","featureList": ["35+ data points per job extraction","Verified company information from LinkedIn","Contact information (emails, phones, social links)","Salary transparency with currency details","Skills taxonomy and requirements","Remote/hybrid work detection","Employee count and company ratings","95+ country coverage worldwide","Export to JSON, CSV, Excel formats","API integration ready for automation"],"keywords": "linkedin scraper, linkedin jobs api, linkedin job listings, linkedin salary data, linkedin data extraction, linkedin job search, linkedin automation, linkedin recruiting, talent intelligence, hr tech, workforce analytics, job market data, professional network scraper, career data, employment trends, recruitment automation, labor market intelligence, job aggregation, skills analysis, company research","aggregateRating": {"@type": "AggregateRating","ratingValue": "4.9","ratingCount": "500","bestRating": "5"},"author": {"@type": "Organization","name": "cheapget","url": "https://apify.com/cheapget?fpr=aiagentapi"},"softwareVersion": "1.0","datePublished": "2024-01-01","dateModified": "2025-12-30"}
🚀 Performance Tips
Optimize your extraction runs for speed, cost, and data quality with these best practices:
💰 Cost Optimization
- Test First: Start with 1-2 search terms and
max_results: 10to verify output quality before scaling - Precise Keywords: Use specific job titles (e.g., "Senior Frontend Engineer" vs. "Developer") for more relevant results
- Monitor Usage: Each job costs $0.00296—check the Usage tab in Apify Console for real-time cost tracking
⚡ Speed Optimization
- Batch Processing: Process multiple search terms in a single run to maximize efficiency
- Recent Posts: Use "1 week" or "24 hours" filters for faster results and fresher job data
- Location Specificity: Specify metro areas (e.g., "San Francisco Bay Area") for better targeting and faster searches
🛡️ Data Quality Tips
- Country Names: Use exact country names as they appear in the dropdown (e.g., "United States", not "USA")
- Fresh Data: LinkedIn job postings are highly dynamic—schedule daily or weekly runs for time-sensitive recruiting
- Salary Availability: Salary data varies by region—US jobs (especially CA, CO, NY) have higher disclosure rates due to transparency laws
- Company Verification: All company data comes from verified LinkedIn company pages for authenticity
📊 Best Practices
- Rate Limits: The Actor handles rate limiting automatically with intelligent proxy rotation
- Data Freshness: All metrics are captured at extraction time—engagement and applicant data reflect real-time values
- Remote Filtering: Use
is_remoteorwork_from_homefields to filter remote-friendly positions post-extraction
❓ FAQ
What job data can I extract?
You can extract comprehensive job listings with 35+ fields including job title, description, salary ranges, contact info (emails, phones), social links, required skills, company information (ratings, employee count, revenue), location details, remote work options, and posting dates.
How many jobs can I extract?
There's no hard limit. You can set max_results to any value (minimum 10). Each search term will return up to the specified number of results. For example, 3 search terms with max_results: 100 can return up to 300 jobs.
Which countries are supported?
The Actor supports 95+ countries including United States, United Kingdom, Canada, Australia, Germany, India, France, Singapore, and many more. See the country dropdown in the input schema for the complete list.
How accurate is the salary data?
Salary data comes directly from employer disclosures on LinkedIn. Accuracy is 100% for disclosed salaries. However, not all jobs include salary information—availability varies by country, industry, and local pay transparency laws.
Can I filter by remote jobs only?
The Actor extracts all matching jobs. You can filter results after extraction using the is_remote (boolean) or work_from_home (string: "remote", "hybrid", "on-site") fields in the output data.
What date formats are supported for posted_since?
The Actor supports both relative formats ("1 week", "30 days", "2 months", "1 year") and absolute dates ("2024-12-01", "2025-01-15"). Relative formats are recommended for recurring scheduled runs.
How long does processing take?
Processing time depends on the number of search terms and max_results. Typical benchmarks:
- 1 search term, 10 results: 30-60 seconds
- 3 search terms, 100 results each: 2-4 minutes
- 5 search terms, 200 results each: 5-8 minutes
What output formats are available?
The Actor outputs data in JSON format by default. You can export results to CSV or Excel formats using Apify's dataset export features in the Output tab.
Why are some company fields empty?
Company data availability depends on whether the employer has a complete LinkedIn company page. Verified companies with active LinkedIn presence have the most complete data (ratings, employee counts, revenue, etc.).
🏷️ LinkedIn Job Search
🔥 Search Terms: linkedin scraper, linkedin jobs api, linkedin job listings, linkedin salary data, linkedin data extraction, linkedin job search, linkedin automation, linkedin job aggregator, linkedin job parser, linkedin career data, linkedin talent intelligence, linkedin recruiting api, linkedin hiring data, linkedin company insights, linkedin employee data, linkedin skills extraction, linkedin job feed, professional network scraper, b2b job data, enterprise recruiting data, hr tech api, workforce analytics, employment trends, job market intelligence, talent acquisition, recruitment automation, labor market data, career platform, job board scraper, professional jobs api
💼 Use Case: talent-intelligence recruiting-automation labor-market-analytics competitive-hiring-analysis workforce-planning career-platform hr-tech talent-acquisition skills-gap-analysis salary-benchmarking company-research headcount-planning job-matching-ai recruitment-analytics employment-trends job-aggregation market-intelligence candidate-sourcing employer-branding hiring-insights professional-data career-coaching job-board-integration talent-marketplace workforce-intelligence recruitment-platform job-search-engine career-analytics
⚖️ Legal & Compliance
This actor extracts publicly available data only. It does not bypass authentication, access private content, or violate platform terms of service. You are responsible for:
- Data Rights: Ensuring you have permission to collect and use the extracted data
- Privacy Compliance: Adhering to GDPR, CCPA, and other applicable privacy laws when processing data
- Platform Terms: Respecting the platform's terms of service and usage policies
- Ethical Use: Using extracted data responsibly and in compliance with applicable laws
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Last Updated: January 30, 2026
