LinkedIn Jobs Scraper

Search LinkedIn jobs with hiring filters, then optionally turn each listing into a fuller job record.

LinkedIn Jobs Scraper is my research tool for questions that a single job page cannot answer: which companies are hiring for a role, how demand differs by location, and how experience or workplace filters change the market you see.

Frame the market before collecting it

Begin with a specific keyword and location. Date posted, experience level, job type, workplace, and sorting filters let you define a defensible slice of the market instead of downloading an unexplained pile of listings.

Keyword search

Search jobs by keywords, with an optional location resolved automatically to a LinkedIn geo ID.

Field	Type	Required	Description
keywords	string	Yes	Job search keywords, e.g. a title, skill, or company name.
location	string	No	A place name to search jobs in. Resolved to a LinkedIn geo ID automatically; ignored when geo_id is set.
maxItems	integer	No	Maximum number of job listings to save. Set to 0 for no item limit.

Filtered search

Narrow results with date posted, experience level, job type, workplace type, and sort order.

Field	Type	Required	Description
keywords	string	Yes	Job search keywords, e.g. a title, skill, or company name.
geo_id	string	No	A known LinkedIn geo ID to search jobs in. Overrides location when set.
date_posted	string	No	Only return jobs posted within this window.
experience_levels	array	No	Only return jobs matching these experience levels.
job_types	array	No	Only return jobs matching these employment types.
workplace	string	No	Only return jobs matching this workplace type.
sortBy	string	No	Order jobs by recency or relevance.

Search with enrichment

Enable Enrich jobs to attach applicant counts, criteria, and the full job description to every result.

Field	Type	Required	Description
keywords	string	Yes	Job search keywords, e.g. a title, skill, or company name.
enrichJob	boolean	No	Fetch the full job posting for each result and attach applicants, criteria, and description.

Example market slice

{
  "keywords": "Software Engineer",
  "location": "San Francisco Bay Area",
  "maxItems": 20,
  "enrichJob": false
}

Choose discovery rows or enriched postings

The search result fields are suited to scanning titles, companies, locations, and listing URLs. Turn on job enrichment only when the analysis needs the full posting; it adds depth, but it also changes run cost and processing time.

Job listing

Field	Type	Description
job_id	string	LinkedIn job posting ID.
title	string	Job title.
company	string	Hiring company name.
location	string	Location shown on the profile.
url	string	LinkedIn profile URL for the related profile.
posted_at	string	Job posting date.
posted_label	string	Human-readable posting age, e.g. "8 months ago".

Compensation

Field	Type	Description
salary	mixed	Salary range, when listed.
benefits	mixed	Benefits badge shown on the listing, e.g. "Actively Hiring".

Enriched details

Field	Type	Description
applicants	string	Applicant count label, from job enrichment.
is_active	boolean	Whether the job posting is still active, from job enrichment.
criteria	object	Seniority level, employment type, job function, and industries, from job enrichment.
description_text	string	Plain-text job description, from job enrichment.
description_html	string	HTML job description, from job enrichment.
poster	mixed	Job poster/recruiter info, from job enrichment.
enriched	boolean	Whether a full profile was successfully attached.

Shortened result

{
  "job_id": "4318514364",
  "title": "Software Engineer",
  "company": "Voltai",
  "location": "Palo Alto, CA",
  "url": "https://www.linkedin.com/jobs/view/software-engineer-at-voltai-4318514364",
  "posted_at": "2025-10-22",
  "posted_label": "8 months ago"
}

Three analyses I would build from this dataset

• Compare role demand across locations using the same keyword and filters.
• Track which employers repeatedly open similar positions on a schedule.
• Separate remote, hybrid, and on-site hiring signals before deeper description analysis.

Cost follows the collection strategy

This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab. Enrichment may add extra billable events when enabled.

Apify's free credits may cover small test runs and up to the free result allowance configured for the Actor.

Start with a low maxItems value before enabling enrichment for large runs.

Legal and ethical use

This Actor extracts publicly available LinkedIn profile information. It should not be used to collect private account data, bypass access controls, or contact people in ways that violate privacy laws, LinkedIn terms, or your own compliance obligations. If you are unsure, consult a qualified lawyer.

Run this Actor from code

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")
run = client.actor("thenetaji/linkedin-jobs-scraper").call(run_input={
    "keywords": "Software Engineer",
    "location": "San Francisco Bay Area",
    "maxItems": 20,
    "enrichJob": false
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Node.js

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" });
const run = await client.actor("thenetaji/linkedin-jobs-scraper").call({
  "keywords": "Software Engineer",
  "location": "San Francisco Bay Area",
  "maxItems": 20,
  "enrichJob": false
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Continue from jobs to companies or people

• LinkedIn Company Scraper — Fetch full public LinkedIn company page details — industry, size, headquarters, specialties, similar and affiliated pages, and recent updates — for one or more company handles or URLs.
• LinkedIn Profile Scraper — Fetch full public LinkedIn profile details — headline, location, about, work history, education, articles, and activity — for one or more usernames or profile URLs.
• Facebook Ads Library Scrape — Scrape public Facebook and Instagram ads from Meta Ad Library: search by keyword or Ad Library URL, browse every ad from a known advertiser Page, or find a Page's ID by brand name. Filter by country, status, category, format, platform, and date, and optionally enrich each ad with full details.

Ask the maintainer

Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests.