Linkedin Jobs Scraper

Every LinkedIn job listing, structured and ready for analysis. Salary ranges, company details, full descriptions, and 22+ fields per job. Search multiple titles across multiple locations in one run. 50 jobs in under 30 seconds.

How it works

✨ Why use this scraper?

Spending hours scrolling through LinkedIn job boards? Copy-pasting listings into spreadsheets? Missing salary data because LinkedIn hides it after a few views?

• 💰 Salary data when LinkedIn has it. Min, max, and currency extracted from every listing that shows compensation.
• 🔍 Multi-title, multi-location search. Run "Data Engineer" + "ML Engineer" across "New York" + "London" + "Berlin" in one call. All combinations, deduplicated.
• 📝 Full job descriptions. Complete requirements, responsibilities, and qualifications. Not just the preview card.
• 📧 Email extraction. Contact emails found in job descriptions are extracted automatically.
• 🏢 Company details. Name, logo, industry, LinkedIn URL, and direct apply links.
• ⚡ No login required. Works on public LinkedIn data. No cookies, no account, no API key.
• 🔄 Automatic deduplication. Cross-product searches never return the same job twice.

🎯 Use cases

Team	What they build
Recruiters	Salary benchmarks by role and city to write competitive offers
Job seekers	Automated job feeds matching specific titles, locations, and experience levels
Sales teams	Lists of companies actively hiring in target industries (buying signals)
Market research	Hiring trend reports by role, location, and seniority across markets
Data teams	Structured datasets of job market conditions for modeling and analysis
HR analytics	Competitor job posting monitoring with salary and benefits tracking

📥 Input parameters

Search

Parameter	Type	Default	Description
titles	Array	["Software Engineer"]	Job titles to search. Each title x location runs a separate search
locations	Array	["United States"]	Locations to search. Crossed with every title
maxItems	Integer	50	Maximum number of jobs to return

Filters

Parameter	Type	Description
publishedAt	Select	Posted within: Any time, 24 hours, Past week, Past month
contractType	Select	Full-time, Part-time, Contract, Temporary, Internship, Volunteer
experienceLevel	Select	Internship, Entry Level, Associate, Mid-Senior, Director, Executive
workType	Select	All, On-site, Remote, Hybrid
easyApply	Boolean	Only return jobs with LinkedIn Easy Apply

📊 Output data

{
  "id": "4334158613",
  "title": "Software Engineer, Fullstack",
  "companyName": "Notion",
  "companyUrl": "https://www.linkedin.com/company/notionhq",
  "companyLogo": "https://media.licdn.com/dms/image/...",
  "companyIndustry": "Software Development",
  "location": "San Francisco, CA",
  "city": "San Francisco",
  "state": "CA",
  "country": "United States",
  "isRemote": false,
  "jobUrl": "https://www.linkedin.com/jobs/view/4334158613",
  "jobUrlDirect": "https://notion.com/careers/apply/...",
  "datePosted": "2026-04-01",
  "salaryMin": 150000,
  "salaryMax": 220000,
  "salaryCurrency": "USD",
  "jobType": ["Full-time"],
  "jobLevel": "Mid-Senior level",
  "jobFunction": "Engineering and Information Technology",
  "numApplicants": "Over 100 applicants",
  "description": "We are looking for a talented engineer...",
  "emails": ["careers@notion.com"],
  "easyApply": false,
  "scrapedAt": "2026-04-09T10:30:00Z"
}

🗂️ Data fields

Category	Fields
Job	id, title, description, jobUrl, jobUrlDirect, datePosted, numApplicants, easyApply
Job details	jobType, jobLevel, jobFunction, salaryMin, salaryMax, salaryCurrency
Location	location, city, state, country, isRemote
Company	companyName, companyUrl, companyLogo, companyIndustry
Extracted	emails, scrapedAt

🚀 Examples

Find remote Python jobs in Europe

{
  "titles": ["Python Developer", "Backend Engineer"],
  "locations": ["London", "Berlin", "Amsterdam"],
  "workType": "2",
  "contractType": "F",
  "maxItems": 100
}

Track new data science openings this week

{
  "titles": ["Data Scientist", "ML Engineer", "Data Analyst"],
  "locations": ["United States"],
  "publishedAt": "r604800",
  "maxItems": 200
}

Monitor new full-time openings in multiple cities

{
  "titles": ["Software Engineer", "Backend Developer"],
  "locations": ["San Francisco", "New York", "Austin"],
  "contractType": "F",
  "publishedAt": "r86400",
  "maxItems": 100
}

Entry-level jobs with Easy Apply

{
  "titles": ["Junior Developer", "Graduate Engineer"],
  "locations": ["New York", "Chicago"],
  "experienceLevel": "2",
  "easyApply": true,
  "maxItems": 50
}

💻 Integrations

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("silentflow/linkedin-jobs-scraper").call(run_input={
    "titles": ["Software Engineer", "Backend Developer"],
    "locations": ["New York", "San Francisco"],
    "contractType": "F",
    "publishedAt": "r604800",
    "maxItems": 100,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    salary = f"${item['salaryMin']:,}-${item['salaryMax']:,}" if item.get("salaryMin") else "N/A"
    print(f"{item['title']} @ {item['companyName']} | {salary} | {item['location']}")

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('silentflow/linkedin-jobs-scraper').call({
    titles: ['Software Engineer', 'Backend Developer'],
    locations: ['New York', 'San Francisco'],
    contractType: 'F',
    publishedAt: 'r604800',
    maxItems: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => {
    const salary = item.salaryMin ? `$${item.salaryMin.toLocaleString()}-$${item.salaryMax.toLocaleString()}` : 'N/A';
    console.log(`${item.title} @ ${item.companyName} | ${salary} | ${item.location}`);
});

📈 Performance

Metric	Value
Speed	~50 jobs in 20-30 seconds
Max results per run	~1,000 per title/location combo (no hard cap)
Fields per job	22+
No login required	Yes

💡 Tips for best results

1. Use multiple titles to cover job title variations: ["Python Developer", "Backend Engineer", "Software Developer"]
2. Cross titles with locations to search multiple markets in one run: 3 titles x 3 cities = 9 searches
3. Filter by date with publishedAt: "r604800" to get only jobs from the past week
4. Start with 25 results to test your filters before scaling
5. Combine filters for precision: fulltime + remote + past week gives you only the freshest relevant listings

❓ FAQ

Q: Do I need a LinkedIn account? No. The scraper uses public LinkedIn job listings. No login, no cookies, no API key.

Q: Why are some jobs missing salary data? LinkedIn only shows salary for a subset of listings. The scraper extracts it when present.

Q: What does the titles x locations cross-product mean? If you provide 2 titles and 3 locations, the scraper runs 6 searches (every title in every location) and deduplicates results.

Q: What's the difference between jobUrl and jobUrlDirect? jobUrl is the LinkedIn listing page. jobUrlDirect is the external apply link (when available).

Q: How many jobs can I get per run? LinkedIn returns up to ~1,000 results per title/location combination. Use multiple titles and locations to get more: 3 titles x 3 cities can yield thousands of results in one run.

Q: Can I search globally? Yes. Set locations to ["United States", "United Kingdom", "Germany"] or any combination. LinkedIn handles location resolution.

📬 Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations
• Response time: usually under 24 hours

Check out our other scrapers: SilentFlow on Apify