# LinkedIn Jobs Scraper | $3/1K | No Login (Real-Time) (`apivault_labs/linkedin-jobs-scraper`) Actor Scrape LinkedIn Jobs in real-time — title, company, location, job type, description. No login, no API key required. - **URL**: https://apify.com/apivault\_labs/linkedin-jobs-scraper.md - **Developed by:** [Apivault Labs](https://apify.com/apivault_labs) (community) - **Categories:** Jobs, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 job extracteds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 | $3/1K | Real-Time, No Login Scrape LinkedIn Jobs search results in real-time. Get job title, company, location, job type, posted date, and description. Filter by experience level, job type, remote-only, and date posted. ### ✨ Key Features - 🔄 Real-time — fresh listings, no cache - 🔍 Rich filters: experience level, job type, remote-only, posted-within - 📄 Multi-page — up to 15 pages (~375 jobs) - 🏢 Optional deduplication by company - 🖼️ Company logos included - 🔒 No login, no API key ### Input #### Basic ```json { "keywords": "software engineer", "location": "United States", "maxPages": 3 } ```` #### Remote jobs only, last 24 hours ```json { "keywords": "product manager", "location": "United States", "remote": true, "postedWithin": "day", "maxPages": 5 } ``` #### Executive roles, full-time ```json { "keywords": "Chief Revenue Officer", "experienceLevel": "executive", "jobType": "full_time", "maxPages": 5 } ``` #### Input Parameters | Field | Type | Required | Description | |-------|------|----------|-------------| | `keywords` | string | ✅ | Job title or keywords | | `location` | string | ❌ | City, country, or 'Remote' | | `maxPages` | int | ❌ | Pages to scrape, 1-15 (default: 3). ~25 jobs per page. | | `remote` | bool | ❌ | Filter to remote jobs only (default: false) | | `experienceLevel` | string | ❌ | `any` / `internship` / `entry` / `associate` / `mid_senior` / `director` / `executive` | | `jobType` | string | ❌ | `any` / `full_time` / `part_time` / `contract` / `temporary` / `volunteer` / `internship` | | `postedWithin` | string | ❌ | `any` / `day` / `week` / `month` | | `extractTitle` / `extractCompany` / `extractLocation` / `extractJobType` / `extractDescription` / `extractDate` / `extractCompanyLogo` | bool | ❌ | Toggle fields (all default true) | | `deduplicateCompanies` | bool | ❌ | Keep only one job per company | | `maxConcurrency` | int | ❌ | Parallel page scrapes (default: 2) | | `timeout` | int | ❌ | Timeout per page (default: 120) | ### Output ```json { "success": true, "source": "linkedin", "jobTitle": "Senior Software Engineer", "companyName": "Acme Corp", "location": "San Francisco, CA (Remote)", "jobType": "Full-time", "description": "Join our team to build the next-gen data platform...", "postedDate": "3 days ago", "companyLogo": "https://media.licdn.com/dms/image/...", "jobUrl": "https://www.linkedin.com/jobs/view/3712345678" } ``` ### Use Cases - **Recruiting** — track openings across companies - **B2B lead generation** — companies hiring = active budget - **Competitive intelligence** — which roles are competitors growing? - **Market research** — skill demand trends by location - **Job aggregator** — populate your site with LinkedIn listings ### Pricing - **$0.003 per job** ($3 per 1,000 jobs) - Pay only for unique jobs extracted ### How it works Builds LinkedIn Jobs public search URL with your filters, paginates with `?start=25&start=50...`, scrapes each page through Thunderbit's rendering engine, deduplicates by title+company+location fingerprint. Typical coverage: - 1 page → ~25 jobs - 3 pages → ~60-75 jobs - 10 pages → ~200-250 jobs ### Tips - Use `postedWithin: day` for fresh leads in competitive markets - Combine `remote: true` + broad location like "United States" for remote-friendly roles - Use `experienceLevel: executive` or `director` for high-value B2B prospects - `deduplicateCompanies: true` is perfect for cold email outreach lists # Actor input Schema ## `keywords` (type: `string`): Job title or keywords. Examples: 'software engineer', 'marketing manager'. ## `location` (type: `string`): City, state, country, or 'Remote'. Examples: 'New York', 'United States', 'Remote'. ## `maxPages` (type: `integer`): Number of result pages to scrape (each ~25 jobs). ## `remote` (type: `boolean`): Filter to remote jobs only ## `experienceLevel` (type: `string`): Filter by required experience ## `jobType` (type: `string`): Filter by employment type ## `postedWithin` (type: `string`): Filter by when the job was posted ## `extractTitle` (type: `boolean`): Extract job position title ## `extractCompany` (type: `boolean`): Extract hiring company name ## `extractLocation` (type: `boolean`): Extract job location ## `extractJobType` (type: `boolean`): Full-time / Contract / etc. ## `extractDescription` (type: `boolean`): Extract job description preview ## `extractDate` (type: `boolean`): When the job was posted ## `extractCompanyLogo` (type: `boolean`): Include company logo URL ## `deduplicateCompanies` (type: `boolean`): If enabled, only the first job from each unique company is kept. ## `maxConcurrency` (type: `integer`): Parallel page scrapes (2-3 recommended) ## `timeout` (type: `integer`): Max wait per LinkedIn page ## Actor input object example ```json { "keywords": "software engineer", "location": "United States", "maxPages": 3, "remote": false, "experienceLevel": "any", "jobType": "any", "postedWithin": "any", "extractTitle": true, "extractCompany": true, "extractLocation": true, "extractJobType": true, "extractDescription": true, "extractDate": true, "extractCompanyLogo": true, "deduplicateCompanies": false, "maxConcurrency": 2, "timeout": 120 } ``` # 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": "software engineer", "location": "United States" }; // Run the Actor and wait for it to finish const run = await client.actor("apivault_labs/linkedin-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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": "software engineer", "location": "United States", } # Run the Actor and wait for it to finish run = client.actor("apivault_labs/linkedin-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": "software engineer", "location": "United States" }' | apify call apivault_labs/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apivault_labs/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper | $3/1K | No Login (Real-Time)", "description": "Scrape LinkedIn Jobs in real-time — title, company, location, job type, description. No login, no API key required.", "version": "1.0", "x-build-id": "YuB6KcSeagnxl0Unm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apivault_labs~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apivault_labs-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/apivault_labs~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-apivault_labs-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/apivault_labs~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-apivault_labs-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", "required": [ "keywords" ], "properties": { "keywords": { "title": "Job Keywords", "type": "string", "description": "Job title or keywords. Examples: 'software engineer', 'marketing manager'." }, "location": { "title": "Location", "type": "string", "description": "City, state, country, or 'Remote'. Examples: 'New York', 'United States', 'Remote'." }, "maxPages": { "title": "Pages to scrape", "minimum": 1, "maximum": 15, "type": "integer", "description": "Number of result pages to scrape (each ~25 jobs).", "default": 3 }, "remote": { "title": "Remote-only", "type": "boolean", "description": "Filter to remote jobs only", "default": false }, "experienceLevel": { "title": "Experience Level", "enum": [ "any", "internship", "entry", "associate", "mid_senior", "director", "executive" ], "type": "string", "description": "Filter by required experience", "default": "any" }, "jobType": { "title": "Job Type", "enum": [ "any", "full_time", "part_time", "contract", "temporary", "volunteer", "internship" ], "type": "string", "description": "Filter by employment type", "default": "any" }, "postedWithin": { "title": "Posted within", "enum": [ "any", "day", "week", "month" ], "type": "string", "description": "Filter by when the job was posted", "default": "any" }, "extractTitle": { "title": "Job Title", "type": "boolean", "description": "Extract job position title", "default": true }, "extractCompany": { "title": "Company Name", "type": "boolean", "description": "Extract hiring company name", "default": true }, "extractLocation": { "title": "Job Location", "type": "boolean", "description": "Extract job location", "default": true }, "extractJobType": { "title": "Job Type", "type": "boolean", "description": "Full-time / Contract / etc.", "default": true }, "extractDescription": { "title": "Description Snippet", "type": "boolean", "description": "Extract job description preview", "default": true }, "extractDate": { "title": "Posted Date", "type": "boolean", "description": "When the job was posted", "default": true }, "extractCompanyLogo": { "title": "Company Logo", "type": "boolean", "description": "Include company logo URL", "default": true }, "deduplicateCompanies": { "title": "Keep only one job per company", "type": "boolean", "description": "If enabled, only the first job from each unique company is kept.", "default": false }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 5, "type": "integer", "description": "Parallel page scrapes (2-3 recommended)", "default": 2 }, "timeout": { "title": "Timeout per page (seconds)", "minimum": 30, "maximum": 300, "type": "integer", "description": "Max wait per LinkedIn page", "default": 120 } } }, "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 } } } } } } } } } } ```