# LinkedIn Job Search (`seemuapps/linkedin-job-search`) Actor Search LinkedIn job listings by keyword and location extract title, company, salary, seniority, employment type, and full job description. - **URL**: https://apify.com/seemuapps/linkedin-job-search.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Social media, Jobs - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 1,000 results 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 Job Search Search LinkedIn job listings by keyword and location — extract full job details including title, company, salary, seniority, and job description. ### What you get - Job title, company name, company ID, and posting URL - Job location, seniority level, employment type, and function - Full job description (plain text and formatted HTML) - Salary range (where disclosed) - Number of applicants, posting date, and easy-apply availability - Discovery metadata (keyword, location, filters used) ### Use cases - Job market research and competitive salary benchmarking - Recruiting pipeline sourcing — find open roles at target companies - Lead generation — identify companies actively hiring in a given function - Career coaching and job board aggregation ### How to use 1. Enter a **Keyword** (job title, skill, or search term, e.g. "Head of Growth") 2. Enter a **Location** (city, region, or country, e.g. "New York" or "United States") 3. Optionally set filters: time range, job type, experience level, work arrangement, company 4. Set **Max Items** to cap results (0 = no limit) 5. Run the actor — results appear in the **Dataset** tab 6. Export to JSON, CSV, or Google Sheets ### Filters | Filter | Options | |---|---| | Time Range | Past 24 hours, Past week, Past month | | Job Type | Full-time, Part-time, Contract, Temporary, Internship, Volunteer | | Experience Level | Internship, Entry level, Associate, Mid-Senior level, Director, Executive | | Work Arrangement | On-site, Remote, Hybrid | ### Output format Each dataset record: ```json { "url": "https://www.linkedin.com/jobs/view/...", "jobPostingId": "4400872129", "jobTitle": "Software Engineer", "companyName": "Acme Corp", "jobLocation": "San Francisco, CA", "jobSummary": "We are looking for...", "jobSeniorityLevel": "Mid-Senior level", "jobEmploymentType": "Full-time", "jobIndustries": "Software Development", "jobBasePayRange": "$120,000 - $160,000", "jobPostedDate": "2026-04-22T00:00:00.000Z", "jobNumApplicants": 42, "applyLink": "https://...", "isEasyApply": true, "discoveryInput": { "keyword": "Software Engineer", "location": "San Francisco", ... } } ```` ### Pair with LinkedIn Job Listings Scraper This actor discovers jobs by keyword. To scrape a specific job listing URL you already have, use the **LinkedIn Job Listings Scraper** actor instead. # Actor input Schema ## `keyword` (type: `string`): Job title, skill, or keyword to search for (e.g. 'Software Engineer', 'Head of Growth'). ## `location` (type: `string`): City, region, or country where jobs should be located (e.g. 'San Francisco', 'United States'). ## `country` (type: `string`): Optional ISO country code to narrow results (e.g. 'US', 'GB', 'FR'). ## `timeRange` (type: `string`): Only return jobs posted within this window. ## `jobType` (type: `string`): Filter by employment type. ## `experienceLevel` (type: `string`): Filter by seniority level. ## `remote` (type: `string`): Filter by on-site, remote, or hybrid. ## `company` (type: `string`): Optional company name to restrict search to a specific employer. ## `maxItems` (type: `integer`): Maximum number of job listings to return. Set to 0 for no limit. ## Actor input object example ```json { "keyword": "Software Engineer", "location": "San Francisco", "timeRange": "", "jobType": "", "experienceLevel": "", "remote": "", "maxItems": 0 } ``` # Actor output Schema ## `results` (type: `string`): Each record contains: url, jobPostingId, jobTitle, companyName, companyId, jobLocation, jobSummary, jobSeniorityLevel, jobFunction, jobEmploymentType, jobIndustries, jobBasePayRange, companyUrl, jobPostedTime, jobPostedDate, jobNumApplicants, applyLink, countryCode, titleId, companyLogo, applicationAvailability, baseSalary, isEasyApply, discoveryInput. # 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 = { "keyword": "Software Engineer", "location": "San Francisco" }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/linkedin-job-search").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 = { "keyword": "Software Engineer", "location": "San Francisco", } # Run the Actor and wait for it to finish run = client.actor("seemuapps/linkedin-job-search").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 '{ "keyword": "Software Engineer", "location": "San Francisco" }' | apify call seemuapps/linkedin-job-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/linkedin-job-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Job Search", "description": "Search LinkedIn job listings by keyword and location extract title, company, salary, seniority, employment type, and full job description.", "version": "1.0", "x-build-id": "h1Bdv7X8iDQOgQWnY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~linkedin-job-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-linkedin-job-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~linkedin-job-search/runs": { "post": { "operationId": "runs-sync-seemuapps-linkedin-job-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~linkedin-job-search/run-sync": { "post": { "operationId": "run-sync-seemuapps-linkedin-job-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword", "location" ], "properties": { "keyword": { "title": "Keyword", "type": "string", "description": "Job title, skill, or keyword to search for (e.g. 'Software Engineer', 'Head of Growth')." }, "location": { "title": "Location", "type": "string", "description": "City, region, or country where jobs should be located (e.g. 'San Francisco', 'United States')." }, "country": { "title": "Country Code", "type": "string", "description": "Optional ISO country code to narrow results (e.g. 'US', 'GB', 'FR')." }, "timeRange": { "title": "Time Range", "enum": [ "", "Past 24 hours", "Past week", "Past month" ], "type": "string", "description": "Only return jobs posted within this window.", "default": "" }, "jobType": { "title": "Job Type", "enum": [ "", "Full-time", "Part-time", "Contract", "Temporary", "Internship", "Volunteer", "Other" ], "type": "string", "description": "Filter by employment type.", "default": "" }, "experienceLevel": { "title": "Experience Level", "enum": [ "", "Internship", "Entry level", "Associate", "Mid-Senior level", "Director", "Executive" ], "type": "string", "description": "Filter by seniority level.", "default": "" }, "remote": { "title": "Work Arrangement", "enum": [ "", "On-site", "Remote", "Hybrid" ], "type": "string", "description": "Filter by on-site, remote, or hybrid.", "default": "" }, "company": { "title": "Company", "type": "string", "description": "Optional company name to restrict search to a specific employer." }, "maxItems": { "title": "Max Items", "minimum": 0, "type": "integer", "description": "Maximum number of job listings to return. Set to 0 for no limit.", "default": 0 } } }, "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 } } } } } } } } } } ```