LinkedIn Jobs Scraper Pro

Search LinkedIn job listings by title, location, seniority, work type, and employment type — and export full results to XLSX, CSV, or JSON in minutes.

Whether you're a job seeker targeting senior roles, a recruiter building talent pipelines, or an HR tech team tracking the market — LinkedIn Jobs Scraper Pro gives you structured, actionable job data without manual searching.

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What it does

LinkedIn Jobs Scraper Pro runs multi-location, multi-keyword searches against LinkedIn's job board and returns a clean, structured dataset for every matching role. For each job it captures:

• Job title, company, location
• Date posted
• Easy Apply flag (detected at card level and confirmed on detail page)
• Remote / hybrid flag (detected from title, location, and job description)
• Seniority level and employment type
• Applicant count
• Full job description (up to 5,000 characters)
• Direct job URL
• Which keyword and location found it

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Key features

Multi-location, multi-keyword — run any combination of job titles × locations in a single run. Search "Delivery Director" in India and the United States simultaneously.

Remote & hybrid filter — use LinkedIn's native work type filter to restrict results to Remote only, Hybrid only, On-site only, or all types.

Easy Apply detection — two-layer check: card badge (with 5 selector fallbacks for resilience against LinkedIn HTML changes) plus confirmation on the job detail page.

Rich job details — optionally visits each job page to extract the full description, confirmed seniority, employment type, and applicant count.

Seniority filter — target Internship, Entry, Associate, Mid-Senior, Director, or Executive levels independently.

Employment type filter — filter for Full-time, Part-time, Contract, Temporary, or any combination.

Deduplication — jobs found by multiple keywords or across multiple locations are deduplicated before output.

Proxy support — routes through Apify's proxy network to reduce blocking risk on large runs.

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Input

Field	Type	Default	Description
job_titles	string list	—	Job titles to search (required)
locations	string list	India	LinkedIn location strings
days_posted	integer	30	Only jobs posted within N days
max_jobs_per_keyword	integer	50	Max results per keyword per location
seniority_levels	multi-select	Director, Executive	Seniority filter
work_type	select	All	On-site / Remote / Hybrid / All
employment_types	multi-select	Full-time	Employment type filter
easy_apply_only	boolean	false	Restrict to Easy Apply jobs
fetch_job_details	boolean	true	Visit each job page for full details
use_apify_proxy	boolean	true	Use Apify proxy network

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Example input

{
  "job_titles": [
    "Head of Engineering",
    "VP of Technology",
    "Delivery Director"
  ],
  "locations": [
    "India",
    "United States",
    "United Kingdom"
  ],
  "days_posted": 30,
  "max_jobs_per_keyword": 50,
  "seniority_levels": ["5", "6"],
  "work_type": "2",
  "easy_apply_only": false,
  "fetch_job_details": true,
  "use_apify_proxy": true
}

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Example output

Each job in the dataset looks like this:

{
  "job_id": "3987654321",
  "job_title": "Head of Engineering",
  "company": "Acme Corp",
  "location": "Mumbai, Maharashtra, India",
  "date_posted": "2026-03-15",
  "easy_apply": "Yes",
  "remote_hybrid": "No",
  "seniority_level": "Director",
  "employment_type": "Full-time",
  "applicant_count": "47 applicants",
  "search_keyword": "Head of Engineering",
  "search_location": "India",
  "job_url": "https://in.linkedin.com/jobs/view/...",
  "job_description": "We are looking for a Head of Engineering to..."
}

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Usage tips

For job seekers — run weekly with days_posted: 14 and max_jobs_per_keyword: 50 to catch everything new without re-scraping old posts.

For recruiters — search a broad list of titles across multiple locations. Use the job_description field to filter by skills or stack in your own tooling.

First-time run — use days_posted: 60 and max_jobs_per_keyword: 75 to get a full backlog. Switch to shorter windows for recurring runs.

Remote-only roles globally — set work_type to "Remote only" and add locations like "United States", "United Kingdom", "Europe" to surface roles you can work from anywhere.

Faster runs (no description) — disable fetch_job_details to cut run time by ~60%. You'll still get title, company, location, date, Easy Apply, and URL.

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Performance

Run type	Keywords × Locations	Est. jobs	Est. time
Quick scan (no details)	10 × 2	~500	~10 min
Standard (with details)	10 × 2	~500	~45 min
Deep run (with details)	30 × 4	~2,000+	~3 hrs

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Limitations

• LinkedIn may require login for some job detail pages. Jobs behind an auth wall will have job_description: "Login required" but all card-level fields are still captured.
• LinkedIn's HTML structure changes periodically. The scraper uses multi-selector fallbacks and text-based detection to stay resilient, but occasional updates may be needed.
• This scraper is for personal and research use. Please review LinkedIn's Terms of Service before using at scale.

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Output formats

Export your dataset from the Apify console as XLSX, CSV, JSON, or JSONL — or connect directly via the Apify API.