# LinkedIn Jobs Scraper (`brilliant_gum/linkedin-jobs-scraper`) Actor Scrape LinkedIn job listings without login. Search by keyword and location, filter by job type, seniority, work arrangement and date. Get titles, companies, salaries, descriptions, applicant counts and more. No account required. - **URL**: https://apify.com/brilliant\_gum/linkedin-jobs-scraper.md - **Developed by:** [Yuliia Kulakova](https://apify.com/brilliant_gum) (community) - **Categories:** Jobs, Developer tools - **Stats:** 3 total users, 2 monthly users, 71.4% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $15.00 / 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. 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 ![LinkedIn Jobs Scraper](https://i.imgur.com/1INZZCo.png) > **Scrape LinkedIn job listings without login — titles, companies, locations, salaries, seniority levels, applicant counts, full descriptions and more.** No LinkedIn account required. Uses LinkedIn's public guest API — fast, reliable, no browser needed. ### What it does Search LinkedIn job listings by keyword and location. Run multiple searches at once, apply filters, and optionally fetch full job details including salary ranges, seniority level, applicant count and job description. - ✅ No LinkedIn account or login required - ✅ Search multiple job titles in one run - ✅ Filter by job type, seniority, work arrangement and date posted - ✅ Optional full details: salary, description, applicant count, industry - ✅ Built-in deduplication across pages and queries - ✅ Export to JSON, CSV or Excel ### Input | Field | Type | Description | |---|---|---| | `searchQuery` | string | Job title or keywords (e.g. `"software engineer"`) | | `searchQueries` | array | Multiple job titles in one run — overrides `searchQuery` | | `location` | string | City, country or region (e.g. `"New York"`, `"London"`, `"Remote"`) | | `maxResults` | integer | Max jobs to return (default: 50, max: 1000) | | `datePosted` | string | `any` · `past24h` · `pastWeek` · `pastMonth` | | `jobType` | array | `fulltime` · `parttime` · `contract` · `temporary` · `internship` · `volunteer` | | `seniorityLevel` | array | `internship` · `entry` · `associate` · `mid_senior` · `director` · `executive` | | `workType` | array | `onsite` · `remote` · `hybrid` | | `includeDescription` | boolean | Fetch full details per job (salary, description, applicants). Default: `false` | | `deduplication` | boolean | Skip duplicate job postings. Default: `true` | ### Output fields | Field | Description | |---|---| | `title` | Job title | | `company` | Company name | | `companyUrl` | LinkedIn company page URL | | `companyLogo` | Company logo image URL | | `location` | Job location | | `postedDate` | Date posted (ISO format) | | `jobUrl` | Direct link to the LinkedIn job posting | | `salaryText` | Salary as shown on the listing | | `salaryMin` / `salaryMax` | Parsed salary range | | `salaryCurrency` | Currency (USD, EUR, GBP…) | | `salaryPeriod` | `yearly` / `hourly` / `monthly` | | `seniorityLevel` | Entry level, Mid-Senior, Director, etc. | | `employmentType` | Full-time, Part-time, Contract, etc. | | `jobFunction` | Job category (Engineering, Sales, etc.) | | `industries` | Industry sector | | `applicantCount` | Number of applicants (when shown) | | `description` | Full job description text | > `salaryMin`, `salaryMax`, `seniorityLevel`, `employmentType`, `jobFunction`, `industries`, `applicantCount` and `description` require **Include Full Details** (`includeDescription: true`). ### Example input ```json { "searchQuery": "data analyst", "location": "New York", "maxResults": 100, "datePosted": "pastWeek", "jobType": ["fulltime"], "workType": ["remote", "hybrid"], "seniorityLevel": ["entry", "mid_senior"], "includeDescription": true } ```` **Multiple searches in one run:** ```json { "searchQueries": ["data analyst", "data scientist", "business analyst"], "location": "United States", "maxResults": 50, "workType": ["remote"] } ``` ### Pricing **$15.00 per 1,000 results** — approximately $0.015 per job listing. | Run | Results | Cost | |---|---|---| | 1 search · 50 jobs | 50 | ~$0.75 | | 3 searches · 100 jobs each | 300 | ~$4.50 | | 5 searches · 200 jobs each | 1,000 | ~$15.00 | Pay only for what you scrape — no subscriptions, no monthly plans. # Actor input Schema ## `searchQuery` (type: `string`): Job title or keywords to search for (e.g. 'software engineer', 'marketing manager', 'data analyst'). ## `searchQueries` (type: `array`): Search for multiple job titles in one run. Overrides searchQuery if provided. ## `location` (type: `string`): City, country or region (e.g. 'New York', 'United States', 'London', 'Remote'). ## `maxResults` (type: `integer`): Maximum number of jobs to return per query. ## `datePosted` (type: `string`): Only include jobs posted within this timeframe. ## `jobType` (type: `array`): Filter by employment type. Leave empty for all. ## `seniorityLevel` (type: `array`): Filter by experience level: internship · entry · associate · mid\_senior · director · executive. Leave empty for all. ## `workType` (type: `array`): Filter by work arrangement: onsite · remote · hybrid. Leave empty for all. ## `includeDescription` (type: `boolean`): Fetch full job description, salary, seniority, applicant count and industry for each listing. Slower — recommended for up to 200 results. ## `deduplication` (type: `boolean`): Skip duplicate job postings across pages and queries. ## Actor input object example ```json { "searchQuery": "software engineer", "location": "United States", "maxResults": 50, "datePosted": "any", "includeDescription": false, "deduplication": true } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "searchQuery": "software engineer", "location": "United States" }; // Run the Actor and wait for it to finish const run = await client.actor("brilliant_gum/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 = { "searchQuery": "software engineer", "location": "United States", } # Run the Actor and wait for it to finish run = client.actor("brilliant_gum/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 '{ "searchQuery": "software engineer", "location": "United States" }' | apify call brilliant_gum/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=brilliant_gum/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "Scrape LinkedIn job listings without login. Search by keyword and location, filter by job type, seniority, work arrangement and date. Get titles, companies, salaries, descriptions, applicant counts and more. No account required.", "version": "1.0", "x-build-id": "9refURXXcgKcrmaMP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/brilliant_gum~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-brilliant_gum-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/brilliant_gum~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-brilliant_gum-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/brilliant_gum~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-brilliant_gum-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Job Title / Keywords", "type": "string", "description": "Job title or keywords to search for (e.g. 'software engineer', 'marketing manager', 'data analyst')." }, "searchQueries": { "title": "Multiple Search Queries", "type": "array", "description": "Search for multiple job titles in one run. Overrides searchQuery if provided.", "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "City, country or region (e.g. 'New York', 'United States', 'London', 'Remote').", "default": "United States" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of jobs to return per query.", "default": 50 }, "datePosted": { "title": "Date Posted", "enum": [ "any", "past24h", "pastWeek", "pastMonth" ], "type": "string", "description": "Only include jobs posted within this timeframe.", "default": "any" }, "jobType": { "title": "Job Type", "uniqueItems": true, "type": "array", "description": "Filter by employment type. Leave empty for all.", "items": { "type": "string", "enum": [ "fulltime", "parttime", "contract", "temporary", "internship", "volunteer", "other" ] } }, "seniorityLevel": { "title": "Seniority Level", "uniqueItems": true, "type": "array", "description": "Filter by experience level: internship · entry · associate · mid_senior · director · executive. Leave empty for all.", "items": { "type": "string", "enum": [ "internship", "entry", "associate", "mid_senior", "director", "executive" ] } }, "workType": { "title": "Work Type", "uniqueItems": true, "type": "array", "description": "Filter by work arrangement: onsite · remote · hybrid. Leave empty for all.", "items": { "type": "string", "enum": [ "onsite", "remote", "hybrid" ] } }, "includeDescription": { "title": "Include Full Details", "type": "boolean", "description": "Fetch full job description, salary, seniority, applicant count and industry for each listing. Slower — recommended for up to 200 results.", "default": false }, "deduplication": { "title": "Remove Duplicates", "type": "boolean", "description": "Skip duplicate job postings across pages and queries.", "default": true } } }, "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 } } } } } } } } } } ```