# LinkedIn Jobs Scraper (`reefapi/linkedin-jobs-scraper`) Actor Scrape LinkedIn job postings as clean JSON โ€” search jobs by keyword, location, date posted, experience, job type, workplace, salary, company and industry, plus full job detail, company profiles, jobs-by-company and similar jobs. No LinkedIn login needed. Job postings only, no personal data. - **URL**: https://apify.com/reefapi/linkedin-jobs-scraper.md - **Developed by:** [ReefAPI](https://apify.com/reefapi) (community) - **Categories:** Jobs, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## LinkedIn Jobs Scraper โ€” Search Job Postings as JSON (No Login) > ๐Ÿ“ฎ **Need help, hit a problem, want a new feature, or a field that's missing from the output?** Email **support@reefapi.com** or open an issue on the **Issues** tab of this Actor โ€” we reply fast and take feature requests seriously. Scrape **LinkedIn job postings** as clean, structured JSON. Search jobs by **keyword, location, date posted, experience level, job type, workplace (remote / hybrid / on-site), salary, company and industry** โ€” then optionally pull the **full job description**, the **employer's company profile**, **all jobs at a company**, or **similar jobs**. **No LinkedIn login, no cookies, no account** โ€” just send a query and get the data. **Job postings only โ€” no personal data** (recruiter / poster info is dropped). ### What is the LinkedIn Jobs Scraper? The LinkedIn Jobs Scraper is a **LinkedIn jobs data API** that turns LinkedIn's public job search into a downloadable dataset. Instead of clicking through pages or fighting login walls, you send a job title and location and get back every matching posting as flat JSON, CSV or Excel โ€” with the company, location, workplace type, posting date, salary band and a direct apply URL. It's the fastest way to **scrape LinkedIn jobs** for job boards, market/salary research, recruiting pipelines and hiring analytics. It reads only **public job-posting data** and never touches personal LinkedIn profiles. ### What can this LinkedIn Jobs Scraper do? - ๐Ÿ”Ž **Search jobs** โ€” by keyword + location, with filters for date posted, experience, job type, workplace, salary, company and industry. - ๐Ÿ“„ **Job detail** โ€” the full posting for a job id: description, employment type, seniority, job function, applicant count. - ๐Ÿข **Company profile** โ€” an employer's industry, HQ, size, website, specialties and description. - ๐Ÿข **Jobs by company** โ€” every open posting at a given company. - ๐Ÿ“ **Location search** โ€” turn free-text into LinkedIn geo IDs for precise targeting. - ๐Ÿ” **Similar jobs** โ€” related postings for a given job. ### What data can I extract? `jobs/search` returns one record per posting. Key fields (from real output): | Field | What it is | |---|---| | `job_id` | LinkedIn job id (use it for **Job detail** / **Similar jobs**) | | `title` | Job title | | `company` | Employer object โ€” `name`, `url`, `slug`, `logo` | | `location` | Job location (city, region) | | `workplace_type` | On-site / Remote / Hybrid | | `posted_date` / `posted_relative` | Absolute date + "3 weeks ago" | | `salary` | Salary / pay band when LinkedIn shows it | | `employment_type` | Full-time / Contract / โ€ฆ (with `include_detail`) | | `seniority_level` | Entry / Mid-Senior / โ€ฆ (with `include_detail`) | | `description_text` | Full job description (with `include_detail`) | | `job_url` | Direct link to the posting | > Field availability varies โ€” not every posting lists a salary, workplace type or seniority, and LinkedIn can change its layout. Set `include_detail: true` to fetch description / employment type / seniority per job. ### How do I scrape LinkedIn jobs? 1. Open the Actor and go to the **Input** tab. 2. Keep **Action** = *Search jobs* (the default). 3. Enter **Keywords** (e.g. `python developer`) and a **Location**, then add any filters (date posted, experience, job type, workplace, min salary, company). 4. Set **Max results**, click **Start**, and download the jobs as **JSON, CSV or Excel** from the **Dataset** tab. ### Input ```json { "action": "jobs/search", "keywords": "data engineer", "location": "United States", "workplace": "remote", "date_posted": "week", "salary_min": 120000, "max_results": 100 } ```` - `keywords` (required for search) ยท `location` ยท `max_results` (1โ€“1000). - Filters: `date_posted`, `experience`, `job_type`, `workplace`, `salary_min`, `company`. - `job_id` โ€” for **Job detail** / **Similar jobs**. `company` โ€” for **Jobs by company** / **Company profile**. - `params` โ€” advanced JSON: `industry`, `job_function`, `geoId`, `include_detail`, `include_company`, `cursor`, `page`. ### Output (jobs/search โ€” one item per job) ```json { "job_id": "4425881907", "title": "Data Engineer", "company": { "name": "MegazoneCloud US", "url": "https://www.linkedin.com/company/megazonecloud-us", "slug": "megazonecloud-us", "logo": "https://media.licdn.com/dms/image/.../megazonecloud_us_logo" }, "location": "Rochester, NY", "workplace_type": "On-site", "posted_date": "2026-06-09", "posted_relative": "3 weeks ago", "salary": null, "job_url": "https://www.linkedin.com/jobs/view/data-engineer-at-megazonecloud-us-4425881907" } ``` With `include_detail: true`, each job also carries `description_text`, `employment_type`, `seniority_level` and `job_function`. ### Use cases - **Job boards & aggregators** โ€” feed fresh LinkedIn postings into your own listings. - **Salary & market research** โ€” analyze demand, pay bands and skills by role and region. - **Recruiting & sourcing** โ€” track open roles at target companies and competitors. - **Hiring analytics** โ€” measure posting volume, remote share and seniority mix over time. - **Lead generation** โ€” find companies actively hiring in a niche. ### FAQ **Is there an official LinkedIn jobs API?** LinkedIn's official APIs are partner-gated and don't expose open job search. This Actor reads LinkedIn's **public** job postings as structured JSON โ€” no partnership or login required. **Do I need a LinkedIn account or cookie?** No. It's fully cookieless โ€” you don't provide any login, cookie or account. Just send your query. **How much does it cost?** Billed on Apify's pay-per-result model, benchmarked to be competitive with other LinkedIn jobs scrapers. See the **Pricing** section on this Actor's page for the current rate. **Can I integrate it?** Yes โ€” run it from the Apify **API** or the **Python / Node.js clients**, and connect the output to **Make, Zapier, n8n, Google Sheets, webhooks** or your ATS via Apify integrations. Great for scheduled daily job pulls. **Is it legal to scrape LinkedIn jobs?** This Actor collects only **public job-posting data** (no login, no personal profiles) and **drops recruiter / poster personal data**. Public job listings are business information; you're responsible for how you use the data. This is not legal advice. *** Unofficial โ€” not affiliated with LinkedIn. Public job-posting data only; no personal profiles. # Actor input Schema ## `action` (type: `string`): What to run: search jobs, a single job's detail, a company profile, a company's jobs, location lookup, or similar jobs. ## `keywords` (type: `string`): Job title, skill or keyword to search for (jobs/search). e.g. 'python developer'. ## `location` (type: `string`): Country, region or city (jobs/search). e.g. 'United States', 'Berlin'. ## `max_results` (type: `integer`): How many jobs to return (1โ€“1000). ## `date_posted` (type: `string`): Only jobs posted within this window. ## `experience` (type: `string`): Filter by seniority. ## `job_type` (type: `string`): Employment type. ## `workplace` (type: `string`): On-site / remote / hybrid. ## `salary_min` (type: `integer`): Only jobs paying at least this annual salary (mapped to LinkedIn's nearest band: 40k/60k/80k/100k/120k/140k+). ## `company` (type: `string`): Employer filter / target: company slug, URL or LinkedIn company id. Used by 'Jobs by company' and as a filter on 'Search jobs'; also the target for 'Company profile'. ## `job_id` (type: `string`): A LinkedIn job id (from Search jobs) โ€” for 'Job detail' and 'Similar jobs'. ## `query` (type: `string`): Partial location text for 'Location search' (returns geoIds). e.g. 'United'. ## `params` (type: `object`): Any extra parameters as key/value JSON (industry, job\_function, geoId, include\_detail, include\_company, cursor, page, โ€ฆ). Merged into the request. ## Actor input object example ```json { "action": "jobs/search", "keywords": "python developer", "location": "United States", "max_results": 50, "date_posted": "", "experience": "", "job_type": "", "workplace": "" } ``` # Actor output Schema ## `jobs` (type: `string`): The LinkedIn job postings scraped (one item per job). # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": "python developer", "location": "United States", "max_results": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("reefapi/linkedin-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": "python developer", "location": "United States", "max_results": 50, } # Run the Actor and wait for it to finish run = client.actor("reefapi/linkedin-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": "python developer", "location": "United States", "max_results": 50 }' | apify call reefapi/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=reefapi/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "Scrape LinkedIn job postings as clean JSON โ€” search jobs by keyword, location, date posted, experience, job type, workplace, salary, company and industry, plus full job detail, company profiles, jobs-by-company and similar jobs. No LinkedIn login needed. Job postings only, no personal data.", "version": "0.1", "x-build-id": "vAG62Yh4VRnharqOG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/reefapi~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-reefapi-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/reefapi~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-reefapi-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/reefapi~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-reefapi-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "action": { "title": "Action", "enum": [ "jobs/search", "jobs/detail", "company", "jobs/by-company", "locations/search", "jobs/similar" ], "type": "string", "description": "What to run: search jobs, a single job's detail, a company profile, a company's jobs, location lookup, or similar jobs.", "default": "jobs/search" }, "keywords": { "title": "Keywords", "type": "string", "description": "Job title, skill or keyword to search for (jobs/search). e.g. 'python developer'." }, "location": { "title": "Location", "type": "string", "description": "Country, region or city (jobs/search). e.g. 'United States', 'Berlin'." }, "max_results": { "title": "Max results", "type": "integer", "description": "How many jobs to return (1โ€“1000)." }, "date_posted": { "title": "Date posted", "enum": [ "", "24h", "week", "month" ], "type": "string", "description": "Only jobs posted within this window.", "default": "" }, "experience": { "title": "Experience level", "enum": [ "", "internship", "entry", "associate", "mid_senior", "director", "executive" ], "type": "string", "description": "Filter by seniority.", "default": "" }, "job_type": { "title": "Job type", "enum": [ "", "fulltime", "parttime", "contract", "temporary", "internship", "volunteer" ], "type": "string", "description": "Employment type.", "default": "" }, "workplace": { "title": "Workplace", "enum": [ "", "onsite", "remote", "hybrid" ], "type": "string", "description": "On-site / remote / hybrid.", "default": "" }, "salary_min": { "title": "Min salary (USD/yr)", "type": "integer", "description": "Only jobs paying at least this annual salary (mapped to LinkedIn's nearest band: 40k/60k/80k/100k/120k/140k+)." }, "company": { "title": "Company", "type": "string", "description": "Employer filter / target: company slug, URL or LinkedIn company id. Used by 'Jobs by company' and as a filter on 'Search jobs'; also the target for 'Company profile'." }, "job_id": { "title": "Job id", "type": "string", "description": "A LinkedIn job id (from Search jobs) โ€” for 'Job detail' and 'Similar jobs'." }, "query": { "title": "Query (location search)", "type": "string", "description": "Partial location text for 'Location search' (returns geoIds). e.g. 'United'." }, "params": { "title": "Advanced parameters", "type": "object", "description": "Any extra parameters as key/value JSON (industry, job_function, geoId, include_detail, include_company, cursor, page, โ€ฆ). Merged into the request." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```