# LinkedIn Jobs Scraper (`scrapesmith/linkedin-jobs-scraper`) Actor πŸ”₯ ~$0.06/1K jobs l Scrape LinkedIn job listings by keyword and location. Get company, salary, job type, experience level, full description and apply link. Export to Excel, CSV or JSON. No login no cookies. - **URL**: https://apify.com/scrapesmith/linkedin-jobs-scraper.md - **Developed by:** [Scrape Smith](https://apify.com/scrapesmith) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.06 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 β€” Search, Filter & Full Details Collect **LinkedIn job listings at scale** by keyword and location β€” no login, no cookies, no account needed. Get the full job details: company, location, salary, posting date, seniority, employment type, job function, industries, applicant count, the complete job description, and the apply link. Export everything to **JSON, CSV, or Excel**, or pull it straight from the API. --- ### What you get per job | Field | Example | |---|---| | `title` | Senior Software Engineer | | `company` / `companyUrl` | Notion Β· linkedin.com/company/notion | | `location` / `isRemote` | San Francisco, CA Β· true | | `salary` | $150,000/yr – $190,000/yr *(when listed)* | | `postedDate` | 2026-06-01 | | `seniority` | Mid-Senior level | | `employmentType` | Full-time | | `jobFunction` | Engineering and Information Technology | | `industries` | Software Development | | `applicants` | 177 | | `descriptionText` / `descriptionHtml` | Full job description | | `companyLogo`, `url`, `jobId` | … | ### How to use it 1. Add one or more **search keywords** (e.g. `software engineer`, `registered nurse`). 2. Set a **location** (e.g. `United States`, `London`, `Remote`) β€” or several under **Locations** to collect more. 3. (Optional) Filter by **date posted, job type, experience level, remote/on-site**. 4. Run it. Results stream into the dataset as they're found. #### Get more than ~1,000 jobs per search LinkedIn caps any single search at roughly 1,000 results. Two ways to go bigger: - **Locations** β€” add multiple cities/regions; every keyword runs against each. - **Maximize per location** β€” use **"Maximize results per location"** to re-run the same search across experience levels, job types, date windows, etc. and merge the unique results (several times more for a single location). ### Filters - **Date posted** β€” past 24 hours / week / month - **Job type** β€” full-time, part-time, contract, temporary, internship, … - **Experience level** β€” internship β†’ executive - **Remote / on-site** β€” remote, on-site, hybrid - **Sort by** β€” most relevant or most recent ### Input example ```json { "queries": ["software engineer"], "location": "United States", "datePosted": "week", "experienceLevel": ["mid-senior level"], "scrapeDescription": true, "maxItems": 1000 } ```` ### Output example ```json { "jobId": "4406118990", "title": "Software Engineer, New Grad", "company": "Notion", "companyUrl": "https://www.linkedin.com/company/notion", "location": "San Francisco, CA", "isRemote": false, "postedDate": "2026-06-01", "salary": null, "seniority": "Not Applicable", "employmentType": "Full-time", "jobFunction": "Engineering and Information Technology", "industries": "Software Development", "applicants": 200, "descriptionText": "Who We Are\nNotion is the collaborative workspace…", "url": "https://www.linkedin.com/jobs/view/software-engineer-new-grad-at-notion-4406118990" } ``` ### Notes - **No login or cookies required** β€” only public job data is collected. - A proxy is recommended at higher volume (the default works out of the box); you can also plug in your own proxies. - `salary` is only present when the employer publishes it on the listing. - Built to be reliable: failed fetches are automatically retried so your dataset comes back complete. ### FAQ **Do I need a LinkedIn account?** No. It only reads public listings. **Can it get full descriptions?** Yes β€” on by default. Turn it off for a lighter, faster export of the core fields. **Which countries?** Any LinkedIn location β€” US, UK, EU, remote, worldwide. **What formats can I export?** JSON, CSV, Excel, HTML table, or via API. # Actor input Schema ## `queries` (type: `array`): Job titles or keywords to search, e.g. 'software engineer', 'registered nurse'. ## `location` (type: `string`): Country to search in. For specific cities or regions, use 'Locations' under Advanced configuration. ## `scrapeDescription` (type: `boolean`): Get each job's full description plus seniority, employment type, job function, industries and applicant count. Turn off for a faster, lighter export of the core fields. ## `datePosted` (type: `string`): Only jobs posted within this window. ## `jobType` (type: `array`): Filter by employment type. ## `experienceLevel` (type: `array`): Filter by seniority. ## `remote` (type: `array`): Filter by work arrangement. ## `sortBy` (type: `string`): Result ordering. ## `locations` (type: `array`): Specific cities or regions to search instead of the country above, e.g. 'New York, NY', 'London'. Every keyword is run against each location. Overrides the country selection. ## `maxItems` (type: `integer`): Total number of jobs to collect across all searches. Leave empty for as many as possible. ## `startUrls` (type: `array`): LinkedIn job-search URLs to scrape directly (keyword and location are read from the URL). ## Actor input object example ```json { "queries": [ "software engineer" ], "location": "United States", "scrapeDescription": true, "datePosted": "any", "sortBy": "relevance" } ``` # 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 = { "queries": [ "software engineer" ], "location": "United States" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesmith/linkedin-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "queries": ["software engineer"], "location": "United States", } # Run the Actor and wait for it to finish run = client.actor("scrapesmith/linkedin-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "software engineer" ], "location": "United States" }' | apify call scrapesmith/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesmith/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "πŸ”₯ ~$0.06/1K jobs l Scrape LinkedIn job listings by keyword and location. Get company, salary, job type, experience level, full description and apply link. Export to Excel, CSV or JSON. No login no cookies.", "version": "0.0", "x-build-id": "rHNdXMb0yiNVK6axB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesmith~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesmith-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/scrapesmith~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-scrapesmith-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/scrapesmith~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesmith-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": { "queries": { "title": "Search keywords", "type": "array", "description": "Job titles or keywords to search, e.g. 'software engineer', 'registered nurse'.", "items": { "type": "string" } }, "location": { "title": "Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "India", "Ireland", "Germany", "France", "Spain", "Italy", "Netherlands", "Belgium", "Switzerland", "Austria", "Portugal", "Sweden", "Norway", "Denmark", "Finland", "Poland", "Czech Republic", "Romania", "Hungary", "Greece", "Ukraine", "Turkey", "Israel", "United Arab Emirates", "Saudi Arabia", "Egypt", "South Africa", "Nigeria", "Kenya", "Singapore", "Hong Kong", "Japan", "South Korea", "China", "Malaysia", "Indonesia", "Thailand", "Vietnam", "Philippines", "New Zealand", "Pakistan", "Brazil", "Mexico", "Argentina", "Chile", "Colombia", "Remote", "Worldwide" ], "type": "string", "description": "Country to search in. For specific cities or regions, use 'Locations' under Advanced configuration.", "default": "United States" }, "scrapeDescription": { "title": "Include full job descriptions", "type": "boolean", "description": "Get each job's full description plus seniority, employment type, job function, industries and applicant count. Turn off for a faster, lighter export of the core fields.", "default": true }, "datePosted": { "title": "Date posted", "enum": [ "any", "day", "week", "month" ], "type": "string", "description": "Only jobs posted within this window.", "default": "any" }, "jobType": { "title": "Job type", "type": "array", "description": "Filter by employment type.", "items": { "type": "string", "enum": [ "full-time", "part-time", "contract", "temporary", "internship", "volunteer", "other" ], "enumTitles": [ "Full-time", "Part-time", "Contract", "Temporary", "Internship", "Volunteer", "Other" ] } }, "experienceLevel": { "title": "Experience level", "type": "array", "description": "Filter by seniority.", "items": { "type": "string", "enum": [ "internship", "entry level", "associate", "mid-senior level", "director", "executive" ], "enumTitles": [ "Internship", "Entry level", "Associate", "Mid-Senior level", "Director", "Executive" ] } }, "remote": { "title": "Remote / on-site", "type": "array", "description": "Filter by work arrangement.", "items": { "type": "string", "enum": [ "on-site", "remote", "hybrid" ], "enumTitles": [ "On-site", "Remote", "Hybrid" ] } }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date" ], "type": "string", "description": "Result ordering.", "default": "relevance" }, "locations": { "title": "Locations (for volume)", "type": "array", "description": "Specific cities or regions to search instead of the country above, e.g. 'New York, NY', 'London'. Every keyword is run against each location. Overrides the country selection.", "items": { "type": "string" } }, "maxItems": { "title": "Max total items", "minimum": 1, "type": "integer", "description": "Total number of jobs to collect across all searches. Leave empty for as many as possible." }, "startUrls": { "title": "Start URLs", "type": "array", "description": "LinkedIn job-search URLs to scrape directly (keyword and location are read from the URL).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```