# LinkedIn & Indeed Job Finder (`karan_sharma_23/linkedin-indeed-job-finder`) Actor Apify Actor that collects and normalizes job postings from LinkedIn and Indeed, applies user-defined filters, removes duplicates, and returns structured results with run diagnostics. - **URL**: https://apify.com/karan\_sharma\_23/linkedin-indeed-job-finder.md - **Developed by:** [Karan Sharma](https://apify.com/karan_sharma_23) (community) - **Categories:** AI, Developer tools, Jobs - **Stats:** 5 total users, 2 monthly users, 92.3% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.000045 / actor start 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Actor Folder Reference This folder contains Apify-facing artifacts. 1. `actor.json` - Actor metadata. - Build and run command used by Apify. 2. `input_schema.json` - Apify GUI input form schema (the file Apify uses for Input tab form rendering). 3. `output_schema.json` - Standard JSON Schema for dataset output records (job records and RUN_SUMMARY record). 4. `sample_input.json` - Ready-to-run sample payload for Apify runs. # Actor input Schema ## `keywords` (type: `array`): Mandatory. List of role or skill keywords to search. ## `locations` (type: `array`): Mandatory. List of target locations. ## `minimumExperience` (type: `integer`): Minimum years of experience required. ## `maximumExperience` (type: `integer`): Maximum years of experience allowed. ## `minimumSalary` (type: `integer`): Minimum annual salary filter in local currency units. ## `maximumSalary` (type: `integer`): Maximum annual salary filter in local currency units. ## `employmentType` (type: `array`): Allowed employment types (for example Full Time, Contract). ## `remoteAllowed` (type: `boolean`): Include fully remote jobs. ## `hybridAllowed` (type: `boolean`): Include hybrid work jobs. ## `maxResults` (type: `integer`): Maximum number of final job records to return. ## `enableAIScoring` (type: `boolean`): Enable optional AI enrichment and scoring when provider keys are available. ## `removeDuplicates` (type: `boolean`): Remove duplicate jobs by company/title/location/url matching. ## `includeCompanyResearch` (type: `boolean`): Attempt additional public company enrichment where available. ## `includeHiringManager` (type: `boolean`): Attempt to include recruiter or hiring manager fields where available. ## `includeCompanies` (type: `array`): Only include jobs from these companies. ## `excludeCompanies` (type: `array`): Exclude jobs from these companies. ## `excludeRecruiters` (type: `array`): Exclude jobs posted by these recruiters when recruiter data is available. ## `excludeKeywords` (type: `array`): Exclude jobs containing these keywords in title or description. ## `blacklist` (type: `array`): Global exclusion terms applied across company, title, and description. ## `whitelist` (type: `array`): Prefer/include jobs matching these terms. ## `postedToday` (type: `boolean`): Prioritize jobs posted today. ## `postedThisWeek` (type: `boolean`): Prioritize jobs posted in the last 7 days. ## `postedThisMonth` (type: `boolean`): Prioritize jobs posted in the last 30 days. ## `aiProvider` (type: `string`): AI provider selection: auto, openai, gemini, or none. ## Actor input object example ```json { "keywords": [ "Python", "SDET", "Automation Engineer", "AI Engineer", "LLM Engineer" ], "locations": [ "India", "Remote", "Jaipur", "Noida", "Gurgaon", "Bangalore", "Pune", "Hyderabad" ], "minimumExperience": 3, "maximumExperience": 5, "minimumSalary": 800000, "maximumSalary": 3000000, "employmentType": [ "Full Time" ], "remoteAllowed": true, "hybridAllowed": true, "maxResults": 500, "enableAIScoring": true, "removeDuplicates": true, "includeCompanyResearch": true, "includeHiringManager": false, "postedToday": false, "postedThisWeek": true, "postedThisMonth": false, "aiProvider": "auto" } ```` # Actor output Schema ## `results` (type: `string`): All output records from the default dataset. ## `datasetOverview` (type: `string`): Dataset output with the overview view selected by default. ## `runSummary` (type: `string`): Dataset records that contain run-level diagnostics and counts. ## `files` (type: `string`): All records in the default key-value store. # 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": [ "Python", "SDET", "Automation Engineer", "AI Engineer", "LLM Engineer" ], "locations": [ "India", "Remote", "Jaipur", "Noida", "Gurgaon", "Bangalore", "Pune", "Hyderabad" ], "employmentType": [ "Full Time" ] }; // Run the Actor and wait for it to finish const run = await client.actor("karan_sharma_23/linkedin-indeed-job-finder").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": [ "Python", "SDET", "Automation Engineer", "AI Engineer", "LLM Engineer", ], "locations": [ "India", "Remote", "Jaipur", "Noida", "Gurgaon", "Bangalore", "Pune", "Hyderabad", ], "employmentType": ["Full Time"], } # Run the Actor and wait for it to finish run = client.actor("karan_sharma_23/linkedin-indeed-job-finder").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": [ "Python", "SDET", "Automation Engineer", "AI Engineer", "LLM Engineer" ], "locations": [ "India", "Remote", "Jaipur", "Noida", "Gurgaon", "Bangalore", "Pune", "Hyderabad" ], "employmentType": [ "Full Time" ] }' | apify call karan_sharma_23/linkedin-indeed-job-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=karan_sharma_23/linkedin-indeed-job-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn & Indeed Job Finder", "description": "Apify Actor that collects and normalizes job postings from LinkedIn and Indeed, applies user-defined filters, removes duplicates, and returns structured results with run diagnostics.", "version": "0.0", "x-build-id": "4hLUEaR8ZGJ4UWgml" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/karan_sharma_23~linkedin-indeed-job-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-karan_sharma_23-linkedin-indeed-job-finder", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/karan_sharma_23~linkedin-indeed-job-finder/runs": { "post": { "operationId": "runs-sync-karan_sharma_23-linkedin-indeed-job-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/karan_sharma_23~linkedin-indeed-job-finder/run-sync": { "post": { "operationId": "run-sync-karan_sharma_23-linkedin-indeed-job-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "locations" ], "properties": { "keywords": { "title": "Keywords", "minItems": 1, "type": "array", "description": "Mandatory. List of role or skill keywords to search.", "items": { "type": "string" } }, "locations": { "title": "Locations", "minItems": 1, "type": "array", "description": "Mandatory. List of target locations.", "items": { "type": "string" } }, "minimumExperience": { "title": "Minimum Experience", "minimum": 0, "type": "integer", "description": "Minimum years of experience required.", "default": 3 }, "maximumExperience": { "title": "Maximum Experience", "minimum": 0, "type": "integer", "description": "Maximum years of experience allowed.", "default": 5 }, "minimumSalary": { "title": "Minimum Salary", "minimum": 0, "type": "integer", "description": "Minimum annual salary filter in local currency units.", "default": 800000 }, "maximumSalary": { "title": "Maximum Salary", "minimum": 0, "type": "integer", "description": "Maximum annual salary filter in local currency units.", "default": 3000000 }, "employmentType": { "title": "Employment Type", "type": "array", "description": "Allowed employment types (for example Full Time, Contract).", "items": { "type": "string" } }, "remoteAllowed": { "title": "Remote Allowed", "type": "boolean", "description": "Include fully remote jobs.", "default": true }, "hybridAllowed": { "title": "Hybrid Allowed", "type": "boolean", "description": "Include hybrid work jobs.", "default": true }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of final job records to return.", "default": 500 }, "enableAIScoring": { "title": "Enable AI Scoring", "type": "boolean", "description": "Enable optional AI enrichment and scoring when provider keys are available.", "default": true }, "removeDuplicates": { "title": "Remove Duplicates", "type": "boolean", "description": "Remove duplicate jobs by company/title/location/url matching.", "default": true }, "includeCompanyResearch": { "title": "Include Company Research", "type": "boolean", "description": "Attempt additional public company enrichment where available.", "default": true }, "includeHiringManager": { "title": "Include Hiring Manager", "type": "boolean", "description": "Attempt to include recruiter or hiring manager fields where available.", "default": false }, "includeCompanies": { "title": "Include Companies", "type": "array", "description": "Only include jobs from these companies.", "items": { "type": "string" } }, "excludeCompanies": { "title": "Exclude Companies", "type": "array", "description": "Exclude jobs from these companies.", "items": { "type": "string" } }, "excludeRecruiters": { "title": "Exclude Recruiters", "type": "array", "description": "Exclude jobs posted by these recruiters when recruiter data is available.", "items": { "type": "string" } }, "excludeKeywords": { "title": "Exclude Keywords", "type": "array", "description": "Exclude jobs containing these keywords in title or description.", "items": { "type": "string" } }, "blacklist": { "title": "Blacklist", "type": "array", "description": "Global exclusion terms applied across company, title, and description.", "items": { "type": "string" } }, "whitelist": { "title": "Whitelist", "type": "array", "description": "Prefer/include jobs matching these terms.", "items": { "type": "string" } }, "postedToday": { "title": "Posted Today", "type": "boolean", "description": "Prioritize jobs posted today.", "default": false }, "postedThisWeek": { "title": "Posted This Week", "type": "boolean", "description": "Prioritize jobs posted in the last 7 days.", "default": true }, "postedThisMonth": { "title": "Posted This Month", "type": "boolean", "description": "Prioritize jobs posted in the last 30 days.", "default": false }, "aiProvider": { "title": "AI Provider", "enum": [ "auto", "openai", "gemini", "none" ], "type": "string", "description": "AI provider selection: auto, openai, gemini, or none.", "default": "auto" } } }, "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 } } } } } } } } } } ```