LinkedIn Jobs Scraper Unlimited — Scrape LinkedIn Jobs Without Limits

Scrape LinkedIn job listings at scale with no 1,000-result cap. This Apify Actor extracts unlimited LinkedIn jobs by keyword, company, location, experience level, work type, and date posted — returning structured JSON data including job title, company name, salary, description, apply URL, seniority level, and more.

Whether you're building a job board, sourcing leads for a recruiting agency, monitoring competitor hiring, or feeding an AI/ML training pipeline, this scraper delivers clean, structured LinkedIn jobs data fast.

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Why use this LinkedIn Jobs Scraper?

• Unlimited results — bypasses LinkedIn's 1,000-job cap via automatic time-window slicing.
• No login required — scrapes public LinkedIn guest endpoints; no LinkedIn account or cookies needed.
• Full job details — extracts the complete job description, seniority, employment type, company info, apply URL, salary, and more.
• Company filters — target specific employers by LinkedIn company name or company ID.
• Smart deduplication — removes duplicate listings across overlapping search slices.
• TLS fingerprint spoofing — uses curl_cffi to mimic real Chrome traffic and reduce blocks.
• Residential proxies — built-in support for Apify Residential Proxy.
• Configurable rate limits — tune concurrency and delays to stay safe.
• Multiple export formats — JSON, CSV, Excel, XML, HTML via Apify Dataset.

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Use cases

• Recruiting & sourcing — Build candidate pipelines or monitor open roles by industry.
• Job aggregator platforms — Power your own job board with fresh LinkedIn listings.
• Market & salary research — Track hiring trends, in-demand skills, and compensation benchmarks.
• Competitor intelligence — Monitor which roles competitors are hiring for and where.
• Lead generation — Identify companies actively hiring (a strong buying signal for B2B SaaS).
• AI/ML training data — Generate large, structured datasets of job postings for NLP models.

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How it works

LinkedIn caps any single job search at ~1,000 results. To break that ceiling, this actor:

1. Builds your search query from keywords, location, geoId, companyId, companyName, jobType, workType, experienceLevel, and datePosted.
2. Detects when the result set approaches the 1,000-result wall.
3. Automatically slices the query into smaller time windows until the entire result space is covered.
4. Fetches detail pages in parallel (with concurrency limits and randomized delays).
5. Deduplicates by jobId across slices before pushing to the dataset.

The result: a complete, clean dataset of every LinkedIn job that matches your filters — far beyond what the LinkedIn UI exposes.

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Input schema

Configure the scraper with the following fields. Only keywords is typically needed for a basic run; all other fields are optional filters.

Field	Type	Default	Description
keywords	string	"python developer"	Job search keywords (e.g., "data engineer", "product manager", "react developer").
location	string	"United States"	Free-text location (e.g., "San Francisco", "Remote", "London, UK").
geoId	string	—	LinkedIn geoId for precise location targeting. Overrides location when provided. Find it in the LinkedIn search URL.
companyName	array of string	[]	Filter by employer names (e.g., ["Google", "Microsoft"]). Leave empty for all companies.
companyId	array of string	[]	Filter by LinkedIn numeric company IDs (e.g., ["1441", "1035"]). Found in the company's LinkedIn URL.
datePosted	enum string	"anyTime"	One of: anyTime, pastMonth, pastWeek, past24Hours.
workType	array of string	[]	Workplace filter: onSite, remote, hybrid.
jobType	array of string	[]	Employment type: fullTime, partTime, contract, temporary, volunteer, internship.
experienceLevel	array of string	[]	Seniority: internship, entryLevel, associate, midSenior, director, executive.
maxResults	integer	100	Maximum jobs to scrape. Set 0 for unlimited.
scrapeJobDetails	boolean	true	Fetch full job descriptions per listing. Slower, but returns richer data.
maxConcurrency	integer	5	Max parallel detail-page requests (1–20).
minDelay	integer	1000	Minimum delay between requests in milliseconds (≥ 500).
maxDelay	integer	3000	Maximum delay between requests in milliseconds (≥ 1000).
proxyConfig	object	Apify Residential	Apify Proxy configuration. Residential strongly recommended.

Example input

{
  "keywords": "python developer",
  "location": "United States",
  "companyName": ["Google", "Microsoft"],
  "datePosted": "pastWeek",
  "workType": ["remote", "hybrid"],
  "jobType": ["fullTime"],
  "experienceLevel": ["midSenior", "director"],
  "maxResults": 0,
  "scrapeJobDetails": true,
  "maxConcurrency": 5,
  "minDelay": 1000,
  "maxDelay": 3000,
  "proxyConfig": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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Output schema

Each item pushed to the Apify Dataset is a flat JSON object with the following fields:

Field	Type	Description
jobId	string	LinkedIn's unique numeric job ID.
title	string	Job title.
companyName	string | null	Employer name.
companyId	string | null	LinkedIn numeric company ID.
companyUrl	string | null	Link to the company's LinkedIn page.
location	string | null	Job location (e.g., "San Francisco, CA").
postedTime	string | null	Human-readable posting time (e.g., "2 days ago").
publishedAt	string | null	ISO timestamp when the job was first posted.
applicationsCount	string | null	Number of applicants (e.g., "42 applicants").
workType	string | null	Remote, Hybrid, or On-site.
experienceLevel	string | null	Seniority (e.g., "Mid-Senior level").
contractType	string | null	Employment type (e.g., "Full-time").
description	string | null	Full job description text (when scrapeJobDetails is true).
jobUrl	string	Canonical LinkedIn job URL.
applyUrl	string | null	External or LinkedIn apply URL.
applyType	string | null	EasyApply, OffsiteApply, etc.
benefits	string | null	Benefits text when present.
sector	string | null	Industry / sector.
salary	string | null	Salary range when published.

Example output

{
  "jobId": "3912345678",
  "title": "Senior Python Developer",
  "companyName": "Acme Corp",
  "companyId": "1441",
  "companyUrl": "https://www.linkedin.com/company/acme",
  "location": "San Francisco, CA",
  "postedTime": "2 days ago",
  "publishedAt": "2026-05-20T10:14:00.000Z",
  "applicationsCount": "42 applicants",
  "workType": "Remote",
  "experienceLevel": "Mid-Senior level",
  "contractType": "Full-time",
  "description": "We are looking for a Senior Python Developer to join our platform team...",
  "jobUrl": "https://www.linkedin.com/jobs/view/3912345678",
  "applyUrl": "https://acme.com/careers/senior-python-developer",
  "applyType": "OffsiteApply",
  "benefits": "Medical, dental, 401(k), unlimited PTO",
  "sector": "Software Development",
  "salary": "$160,000 – $210,000/yr"
}

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Pricing & cost estimate

With Apify Residential Proxy at ~$0.50 per 1,000 requests:

• ~2 requests per job (1 search page covers ~25 jobs + 1 detail page).
• ≈ $0.001 per job at steady state with scrapeJobDetails: true.
• Run without detail pages to lower cost ~10x (only summary fields returned).

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Export formats

The Apify Dataset can be downloaded in:

• JSON — full structured output (default).
• CSV / Excel (XLSX) — ready for spreadsheets and BI tools.
• XML / HTML / RSS — for integrations.

You can also stream results live via the Apify API or push them to webhooks, S3, BigQuery, or Google Sheets via Apify Integrations.

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Tips for better results

• Use geoId for precise locations. Free-text locations occasionally match the wrong city.
• Combine companyName + datePosted: pastWeek to monitor hiring at specific employers.
• Set maxResults: 0 for full coverage; the slicing logic handles the 1,000-result cap automatically.
• Lower maxConcurrency and raise minDelay / maxDelay if you see rate-limit errors.
• Always use residential proxies for large runs to avoid datacenter IP blocks.

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FAQ

Does this scraper require a LinkedIn account or cookies? No. It uses LinkedIn's public guest job endpoints — no login, no cookies, no LinkedIn API key.

How is the 1,000-result limit bypassed? LinkedIn returns at most ~1,000 jobs per query. When a search would exceed that, the actor automatically slices the query into smaller time windows and merges + deduplicates the results.

Can I scrape jobs from a specific company? Yes. Use the companyName array (e.g., ["Google", "Stripe"]) or companyId array for exact LinkedIn company IDs.

Can I scrape remote-only or hybrid jobs? Yes. Set workType to ["remote"], ["hybrid"], or ["remote", "hybrid"].

Can I export results to Google Sheets, S3, or BigQuery? Yes. Use Apify Integrations or download the dataset as JSON, CSV, or Excel.

Is this legal? This actor scrapes publicly accessible LinkedIn job listings (guest endpoints, no login). It collects no personal data beyond publicly posted job information. Always check LinkedIn's Terms of Service and your jurisdiction's data-collection laws before running large jobs.

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Development

pip install -e ".[dev]"
make lint          # ruff check
make typecheck     # mypy --strict
make test          # pytest
make all           # lint + typecheck + test

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Support & feedback

Found a bug or want a new feature? Open an issue on the Apify Actor page. Pull requests welcome.