# LinkedIn Jobs (`schesds/linkedin-jobs`) Actor Find all LinkedIn jobs listed by a company ID or company jobs URL, with structured job details. - **URL**: https://apify.com/schesds/linkedin-jobs.md - **Developed by:** [Tedd Shesden](https://apify.com/schesds) (community) - **Categories:** Jobs, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $5.00 / 1,000 linkedin jobs 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 Find all jobs listed by a LinkedIn company ID or company jobs URL and return structured job details. Use this Actor to collect job listings for recruiting intelligence, labor-market research, sales prospecting, competitive hiring analysis, and company job monitoring. ### What You Can Extract - Job title, job URL, and job ID - Company name, company URL, and logo URL when available - Location, workplace type, employment type, seniority, function, and industries - Job description, post date, salary, skills, and criteria when available - Clear diagnostic rows for inputs that could not be extracted ### Use Cases - Track open roles for a target company - Build company hiring datasets by LinkedIn company ID - Monitor hiring activity across companies - Export jobs to spreadsheets, BI tools, CRMs, or data warehouses ### Input Add one or more LinkedIn company IDs or LinkedIn company jobs/search URLs. The Actor returns all jobs found for each company input. #### Example Inputs Find jobs by LinkedIn company ID: ```json { "companyInputs": [ "30898036" ] } ```` Find jobs from a LinkedIn company jobs URL: ```json { "companyInputs": [ "https://www.linkedin.com/jobs/search/?f_C=30898036" ] } ``` ### Output Each delivered job is emitted as one `linkedin_job` row. Failed inputs are emitted as `scrape_error` rows with `failureStage` and `errorMessage`. The main output columns include `id`, `publishedAt`, `postedTime`, `title`, `jobUrl`, `companyName`, `companyId`, `companyUrl`, `location`, `contractType`, `experienceLevel`, `workType`, `sector`, `description`, `companyLogo`, and `jobQuality`. Results can be exported from Apify as JSON, CSV, Excel, XML, RSS, or HTML. ### Pricing When pay-per-event monetization is enabled, the Actor charges one event for each delivered `linkedin_job` row. Failed inputs and diagnostic rows are not charged. Because company job discovery returns all jobs found for each company input, the final run cost depends on the number of jobs available for those companies. The Actor charges for every delivered `linkedin_job` row so the billing unit always matches the extracted data. ### Notes - Availability and field coverage depend on what LinkedIn exposes for each job. - Company job discovery can return variable volumes depending on the company and LinkedIn availability. - The public company discovery mode intentionally does not expose a result limit. The Actor returns and charges for all delivered job rows so the billing unit matches the extracted data. - Keyword-based discovery is not exposed in the public v1 because generic keyword searches can produce unpredictable upstream volumes. # Actor input Schema ## `companyInputs` (type: `array`): Add LinkedIn company IDs or company jobs/search URLs. The Actor returns all jobs found for each company input. Example company ID: 30898036. Example URL: https://www.linkedin.com/jobs/search/?f\_C=30898036 ## Actor input object example ```json { "companyInputs": [ "30898036" ] } ``` # Actor output Schema ## `results` (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 = { "companyInputs": [ "30898036" ] }; // Run the Actor and wait for it to finish const run = await client.actor("schesds/linkedin-jobs").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 = { "companyInputs": ["30898036"] } # Run the Actor and wait for it to finish run = client.actor("schesds/linkedin-jobs").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 '{ "companyInputs": [ "30898036" ] }' | apify call schesds/linkedin-jobs --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=schesds/linkedin-jobs", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs", "description": "Find all LinkedIn jobs listed by a company ID or company jobs URL, with structured job details.", "version": "0.1", "x-build-id": "oMPofA0cyJCV3s6m9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/schesds~linkedin-jobs/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-schesds-linkedin-jobs", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/schesds~linkedin-jobs/runs": { "post": { "operationId": "runs-sync-schesds-linkedin-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/schesds~linkedin-jobs/run-sync": { "post": { "operationId": "run-sync-schesds-linkedin-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companyInputs" ], "properties": { "companyInputs": { "title": "LinkedIn company IDs or jobs URLs", "type": "array", "description": "Add LinkedIn company IDs or company jobs/search URLs. The Actor returns all jobs found for each company input. Example company ID: 30898036. Example URL: https://www.linkedin.com/jobs/search/?f_C=30898036", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```