# Indeed Jobs Scraper | Real-Time Job Listings API (`b2b_leads/indeed-job-real-time-data-scraper`) Actor Indeed job scraper for recruiters & job boards. Collect real-time postings by keyword, location, company & URL. Full descriptions, salary, filters, structured JSON. Hiring data for market research, talent sourcing, AI agents, Zapier & webhooks. Fast parallel Apify actor. - **URL**: https://apify.com/b2b\_leads/indeed-job-real-time-data-scraper.md - **Developed by:** [Chidubem Aneke](https://apify.com/b2b_leads) (community) - **Categories:** Jobs, Developer tools, MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.50 / 1,000 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 ## Indeed Job Real-Time Data **The fastest way to collect Indeed job postings on Apify.** Turn any job search into clean, structured JSON — ready for spreadsheets, dashboards, automations, and AI workflows. Results land in your dataset **in real time**, as each job is found. Built for recruiters, talent teams, job boards, market researchers, and builders who need **reliable hiring data at scale** — without slow setups or messy exports. --- ### Why this Actor | | Indeed Job Real-Time Data | Typical job data tool | |---|---------------------------|------------------------| | **Speed** | ~1–3 s per job | 5–15 s per job | | **Memory** | **256–512 MB** default | 2–4 GB+ | | **Setup** | Run in seconds | Often complex configuration | | **Cost** | Low compute, efficient runs | High | | **Output** | Structured JSON, LLM-ready | Often messy or incomplete | | **Scale** | Up to **1,000 jobs** per keyword | Often capped lower | | **Filters** | Full Indeed Jobs filters | Often keyword-only | | **Modes** | Search · Company jobs · Job links | Usually one mode only | --- ### Three ways to collect jobs | Mode | What it does | Best for | |------|--------------|----------| | **Job search** | Keyword + location search with full Indeed filters | Market scans, role tracking, location-based hiring | | **Company jobs** | All open roles from specific employers | Competitor monitoring, account-based recruiting | | **Job links** | Structured data from individual Indeed job URLs | Enriching a list you already have | Enable one or combine all three in a single run. --- ### What you get — every job, fully structured Each record is one job posting with `featureType`, `jobKey`, and `scrapedAt` so you can sort, filter, and join with your own data. | Field | What it tells you | |-------|-------------------| | `title`, `company`, `location`, `workplaceType` | Role, employer, place, remote/hybrid/onsite | | `jobUrl`, `applyUrl`, `companyUrl`, `companyLogo` | Direct links and company branding | | `descriptionText`, `descriptionHtml` | Full job description (when detail fetch is on) | | `seniorityLevel`, `employmentType`, `jobFunction` | How the role is classified | | `salary`, `benefits`, `applicantCount`, `indeedApply` | Compensation signals, perks, and competition | | `companyRating`, `companyReviewCount` | Employer reputation on Indeed | | `listedAtISO`, `postedTimeAgo` | How fresh the listing is | | `searchQuery`, `searchLocation`, `searchCompany`, `position` | Which search produced this row and its rank | | `sponsored`, `newJob` | Listing signals from Indeed | Set `includeRaw: true` if you need extended record data for custom processing. **`featureType` values:** `job` (search) · `company_job` (company jobs) · `scrape_by_url` (job links) --- ### Search like Indeed Jobs — get data like a database Use the **same filters job seekers use on Indeed**: - **Keywords** — one search per keyword (e.g. `warehouse`, `registered nurse`) - **Title** — narrow to a specific role name - **Company** — jobs at Amazon, Walmart, or any employer - **Location** — United States, Ohio, New York, Remote, and more - **Experience level** — entry, mid, senior - **Employment type** — full-time, part-time, contract, temporary, internship - **Workplace** — on-site, remote, hybrid - **Date posted** — any time, past month, week, 3 days, or 24 hours - **Sort** — relevance or most recent - **Radius** — miles around your location - **Volume** — up to **1,000 jobs per keyword** - **Full details** — toggle rich descriptions, benefits, and applicant counts on or off --- ### Use cases — real outcomes - **Recruiting pipelines** — build candidate-ready job lists by role, location, and seniority - **Job boards and aggregators** — feed your product with fresh Indeed listings daily - **Market and salary research** — track who is hiring, where, and for what skills - **Competitive intelligence** — monitor competitor hiring by company and function - **Sales and BD** — spot companies in hiring mode for timely outreach - **Staffing agencies** — track demand by region, role, and employer - **AI assistants and agents** — summarize listings, score fit, draft outreach, or answer hiring questions - **Data warehouses and CRMs** — push JSON into Snowflake, BigQuery, HubSpot, Airtable, or your stack via API --- ### LLM and MCP integration Output is **structured JSON** — ideal for ChatGPT, Claude, Gemini, LangChain, LlamaIndex, CrewAI, and custom agents. No cleanup step. No manual formatting. Just records your model can read. #### Recommended workflow 1. Run the Actor with your keywords, companies, or job links. 2. Pull dataset items via [Apify API](https://docs.apify.com/api/v2), webhook, or export JSON/CSV. 3. Pass records to your LLM, vector store, or automation — one job per row. #### Example: one job record for an LLM prompt ```json { "featureType": "job", "jobKey": "a22fa26470cfb9ad", "title": "Warehouse Supervisor", "company": "Tire Discounters", "location": "Cincinnati, OH 45241", "workplaceType": "On-site", "employmentType": "Full-time", "descriptionText": "The Warehouse Supervisor is responsible for overseeing receiving, stocking and distribution...", "salary": "$18 - $22 an hour", "benefits": ["Health insurance", "401(k)"], "applicantCount": 12, "indeedApply": true, "companyRating": 2.9, "listedAtISO": "2026-07-07T05:00:00.000Z", "postedTimeAgo": "2 days ago", "jobUrl": "https://www.indeed.com/viewjob?jk=a22fa26470cfb9ad", "searchQuery": "warehouse", "searchLocation": "Ohio", "position": 1, "scrapedAt": "2026-07-11T12:00:00.000Z" } ```` #### Apify MCP (Model Context Protocol) Connect the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) so AI assistants can: - **Run** this Actor from natural-language instructions - **Read** job results directly in the chat - **Chain** with other Actors — enrich contacts, send alerts, update spreadsheets **Example MCP conversation:** ``` User: "Find 50 warehouse jobs in Ohio posted this week and summarize top employers" → MCP runs Indeed Job Real-Time Data with jobKeywords, jobLocation=Ohio, jobDatePosted=week → MCP reads dataset items → LLM summarizes hiring trends and top companies ``` #### API quick start ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "enableJobSearch": true, "jobKeywords": ["warehouse"], "jobLocation": "Ohio", "jobDatePosted": "week", "jobsPerQuery": 50, "fetchJobDetails": true }' ``` **Fetch results:** `GET https://api.apify.com/v2/datasets/{datasetId}/items?format=json` **Dataset views in Apify Console:** Overview (core fields) and Full details (includes descriptions) Export as **JSON**, **CSV**, **Excel**, **RSS**, or via **API**. *** ### Input reference #### Job search | Input | Type | Default | Description | |-------|------|---------|-------------| | `enableJobSearch` | boolean | `true` | Turn keyword search on or off | | `jobKeywords` | string\[] | `["software engineer"]` | Search keywords — one run per keyword | | `jobTitle` | string | — | Title filter | | `jobCompany` | string | — | Company filter | | `jobLocation` | string | `"United States"` | Location | | `jobExperienceLevels` | enum\[] | all | entry\_level, mid\_level, senior\_level | | `jobTypes` | enum\[] | all | fulltime, parttime, contract, temporary, internship | | `jobRemote` | enum\[] | all | onsite, remote, hybrid | | `jobDatePosted` | enum | `any` | any, month, week, 3days, day | | `jobSort` | enum | `relevance` | relevance or date | | `jobsPerQuery` | integer | `25` | Max jobs per keyword (1–1000) | | `radiusMiles` | integer | `25` | Search radius in miles (0–100) | #### Company jobs | Input | Type | Default | Description | |-------|------|---------|-------------| | `enableCompanyJobs` | boolean | `false` | Collect jobs from company profiles | | `companyNames` | string\[] | `[]` | Company names (e.g. Amazon, Target) | | `jobsPerCompany` | integer | `25` | Max jobs per company (1–1000) | #### Job links | Input | Type | Default | Description | |-------|------|---------|-------------| | `enableScrapeByUrl` | boolean | `false` | Collect data from individual job links | | `jobUrls` | string\[] | `[]` | Indeed job page URLs | #### Output and global | Input | Type | Default | Description | |-------|------|---------|-------------| | `fetchJobDetails` | boolean | `true` | Full description, benefits, applicant count | | `includeRaw` | boolean | `false` | Attach extended record data | | `webhookUrl` | string | — | Optional URL for real-time record delivery (Zapier, Slack, CRM) | | `webhookFormat` | enum | `json` | `json` (full record) or `slack` (message) | | `country` | string | `us` | Target country market (us, uk, ca, …) | | `maxItems` | integer | `10000` | Max total records across all modes | | `proxyConfiguration` | object | residential US | Connection settings (US residential recommended) | Full schema: **Input** tab on Apify Console or `.actor/input_schema.json` in this repository. *** ### Quick start examples **Warehouse roles in Ohio — full details** ```json { "enableJobSearch": true, "jobKeywords": ["warehouse"], "jobLocation": "Ohio", "jobDatePosted": "week", "jobSort": "date", "jobsPerQuery": 50, "fetchJobDetails": true } ``` **Jobs at a specific company** ```json { "enableJobSearch": true, "jobKeywords": ["associate"], "jobCompany": "Amazon", "jobLocation": "United States", "jobsPerQuery": 100 } ``` **All jobs from employer profiles** ```json { "enableCompanyJobs": true, "companyNames": ["Amazon", "Walmart", "Target"], "jobsPerCompany": 50, "fetchJobDetails": true } ``` **Import specific job links** ```json { "enableScrapeByUrl": true, "jobUrls": [ "https://www.indeed.com/viewjob?jk=YOUR_JOB_KEY" ], "fetchJobDetails": true } ``` **Fresh listings only — fast summary mode** ```json { "enableJobSearch": true, "jobKeywords": ["nurse"], "jobLocation": "Dallas, TX", "jobDatePosted": "day", "jobSort": "date", "jobsPerQuery": 75, "fetchJobDetails": false } ``` **High-volume market scan** ```json { "enableJobSearch": true, "jobKeywords": ["machine learning", "data scientist", "AI engineer"], "jobLocation": "United States", "jobExperienceLevels": ["mid_level", "senior_level"], "jobsPerQuery": 500, "fetchJobDetails": true } ``` *** ### Performance and reliability - **Residential proxy (US recommended)** — best results and consistent throughput. - **Default memory: 512 MB** — enough for high-volume runs with multiple keywords and companies. - **Streaming output** — each job is written to the dataset immediately; nothing is buffered in memory for long runs. - **Webhook delivery** — optionally POST each new record to your URL in real time (dataset is always the primary output). - **Smart search expansion** — automatically broadens coverage when you request large result sets. - **Parallel processing** — multiple keywords, companies, and job details run concurrently for faster results at 512 MB memory. *** ### Limitations and compliance - This is an unofficial tool — not affiliated with Indeed. - Use responsibly and comply with applicable laws and Indeed's Terms of Service. - Some fields (e.g. salary, benefits) appear only when employers publish them. - Listing availability can change; expired postings may return summary data only. *** ### Contact and custom work Need something beyond this Actor? I design and build **custom data solutions** and **full-stack products** for teams that want results — not experiments. **Email:** \ **GitHub:** [github.com/DrunkCodes](https://github.com/DrunkCodes) Reach out for: - **Custom Apify Actors** — any website, job board, or data source - **Indeed and hiring data projects** — pipelines, alerts, and dashboards at scale - **LLM and MCP integrations** — connect your data to ChatGPT, Claude, and agent workflows - **Web apps and automation** — data tools, internal platforms, SaaS products, and client-facing apps - **Any scraping project** — lead generation, market research, monitoring, and enrichment at scale Whether you need a one-off data feed or a production system, I can help you ship it. *** *Indeed Job Real-Time Data · by [DrunkCodes](https://github.com/DrunkCodes)* # Actor input Schema ## `enableJobSearch` (type: `boolean`): Search Indeed Jobs by keyword, title, company, and location with filters. ## `jobKeywords` (type: `array`): Main job search keywords — same as the Indeed Jobs search box. One search per keyword. ## `jobTitle` (type: `string`): Title filter (e.g. "Software Engineer"). Combined with keywords for more precise results. ## `jobCompany` (type: `string`): Company filter — search jobs at a specific company (e.g. "Amazon", "Walmart"). Leave empty for any company. ## `jobLocation` (type: `string`): Location to search jobs in (e.g. "United States", "New York, NY", "Remote"). ## `jobExperienceLevels` (type: `array`): Filter jobs by experience level. ## `jobTypes` (type: `array`): Filter jobs by employment type. ## `jobRemote` (type: `array`): Filter jobs by on-site, remote, or hybrid. ## `jobDatePosted` (type: `string`): Only return jobs posted within this window. ## `jobSort` (type: `string`): Relevance or most recent. ## `jobsPerQuery` (type: `integer`): Maximum jobs to return per keyword (1–1000). ## `radiusMiles` (type: `integer`): Radius around the location for job search. ## `enableCompanyJobs` (type: `boolean`): Collect open positions from specific employers on Indeed. ## `companyNames` (type: `array`): Employer names as listed on Indeed (e.g. "Amazon", "Target", "FedEx"). ## `jobsPerCompany` (type: `integer`): Maximum jobs to return per company (1–1000). ## `enableScrapeByUrl` (type: `boolean`): Collect structured data from individual Indeed job page links. ## `jobUrls` (type: `array`): Indeed job page URLs you want to collect. ## `fetchJobDetails` (type: `boolean`): Include each job's full description, benefits, and applicant count. Slightly slower but much richer. ## `includeRaw` (type: `boolean`): Attach extended record data under the raw field. Larger output. ## `webhookUrl` (type: `string`): Optional. Every record is always saved to the run's dataset — this webhook is an additional real-time push. When set, each new record is also sent to this URL (CRM, Slack, Zapier, Make, Google Sheets). ## `webhookFormat` (type: `string`): json = full record object; slack = Slack-friendly message payload. ## `country` (type: `string`): Target country market (e.g. us, uk, ca, au, de, fr). ## `maxItems` (type: `integer`): Maximum total job records across all enabled modes. ## `proxyConfiguration` (type: `object`): Residential US proxy recommended for best results and consistent throughput. ## Actor input object example ```json { "enableJobSearch": true, "jobKeywords": [ "software engineer" ], "jobTitle": "", "jobCompany": "", "jobLocation": "United States", "jobExperienceLevels": [], "jobTypes": [], "jobRemote": [ "onsite", "remote", "hybrid" ], "jobDatePosted": "any", "jobSort": "relevance", "jobsPerQuery": 25, "radiusMiles": 25, "enableCompanyJobs": false, "companyNames": [], "jobsPerCompany": 25, "enableScrapeByUrl": false, "jobUrls": [], "fetchJobDetails": true, "includeRaw": false, "webhookUrl": "", "webhookFormat": "json", "country": "us", "maxItems": 10000, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # Actor output Schema ## `allResults` (type: `string`): Complete dataset with every job field from this run. ## `overview` (type: `string`): Core job fields table view. ## `full` (type: `string`): All job fields including descriptions. # 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 = { "enableJobSearch": true, "jobKeywords": [ "software engineer" ], "jobTitle": "", "jobCompany": "", "jobLocation": "United States", "jobExperienceLevels": [], "jobTypes": [], "jobRemote": [ "onsite", "remote", "hybrid" ], "jobDatePosted": "any", "jobSort": "relevance", "jobsPerQuery": 25, "radiusMiles": 25, "enableCompanyJobs": false, "companyNames": [], "jobsPerCompany": 25, "enableScrapeByUrl": false, "jobUrls": [], "fetchJobDetails": true, "includeRaw": false, "webhookUrl": "", "country": "us", "maxItems": 10000 }; // Run the Actor and wait for it to finish const run = await client.actor("b2b_leads/indeed-job-real-time-data-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 = { "enableJobSearch": True, "jobKeywords": ["software engineer"], "jobTitle": "", "jobCompany": "", "jobLocation": "United States", "jobExperienceLevels": [], "jobTypes": [], "jobRemote": [ "onsite", "remote", "hybrid", ], "jobDatePosted": "any", "jobSort": "relevance", "jobsPerQuery": 25, "radiusMiles": 25, "enableCompanyJobs": False, "companyNames": [], "jobsPerCompany": 25, "enableScrapeByUrl": False, "jobUrls": [], "fetchJobDetails": True, "includeRaw": False, "webhookUrl": "", "country": "us", "maxItems": 10000, } # Run the Actor and wait for it to finish run = client.actor("b2b_leads/indeed-job-real-time-data-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 '{ "enableJobSearch": true, "jobKeywords": [ "software engineer" ], "jobTitle": "", "jobCompany": "", "jobLocation": "United States", "jobExperienceLevels": [], "jobTypes": [], "jobRemote": [ "onsite", "remote", "hybrid" ], "jobDatePosted": "any", "jobSort": "relevance", "jobsPerQuery": 25, "radiusMiles": 25, "enableCompanyJobs": false, "companyNames": [], "jobsPerCompany": 25, "enableScrapeByUrl": false, "jobUrls": [], "fetchJobDetails": true, "includeRaw": false, "webhookUrl": "", "country": "us", "maxItems": 10000 }' | apify call b2b_leads/indeed-job-real-time-data-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=b2b_leads/indeed-job-real-time-data-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Indeed Jobs Scraper | Real-Time Job Listings API", "description": "Indeed job scraper for recruiters & job boards. Collect real-time postings by keyword, location, company & URL. Full descriptions, salary, filters, structured JSON. Hiring data for market research, talent sourcing, AI agents, Zapier & webhooks. Fast parallel Apify actor.", "version": "0.0", "x-build-id": "p1Hc3Od5dXxhBlkzs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/b2b_leads~indeed-job-real-time-data-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-b2b_leads-indeed-job-real-time-data-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/b2b_leads~indeed-job-real-time-data-scraper/runs": { "post": { "operationId": "runs-sync-b2b_leads-indeed-job-real-time-data-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/b2b_leads~indeed-job-real-time-data-scraper/run-sync": { "post": { "operationId": "run-sync-b2b_leads-indeed-job-real-time-data-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": { "enableJobSearch": { "title": "Job search", "type": "boolean", "description": "Search Indeed Jobs by keyword, title, company, and location with filters.", "default": true }, "jobKeywords": { "title": "Job keywords", "type": "array", "description": "Main job search keywords — same as the Indeed Jobs search box. One search per keyword.", "default": [ "software engineer" ], "items": { "type": "string" } }, "jobTitle": { "title": "Job title", "type": "string", "description": "Title filter (e.g. \"Software Engineer\"). Combined with keywords for more precise results.", "default": "" }, "jobCompany": { "title": "Company", "type": "string", "description": "Company filter — search jobs at a specific company (e.g. \"Amazon\", \"Walmart\"). Leave empty for any company.", "default": "" }, "jobLocation": { "title": "Job location", "type": "string", "description": "Location to search jobs in (e.g. \"United States\", \"New York, NY\", \"Remote\").", "default": "United States" }, "jobExperienceLevels": { "title": "Experience levels", "type": "array", "description": "Filter jobs by experience level.", "items": { "type": "string", "enum": [ "entry_level", "mid_level", "senior_level" ], "enumTitles": [ "Entry level", "Mid level", "Senior level" ] }, "default": [] }, "jobTypes": { "title": "Job types", "type": "array", "description": "Filter jobs by employment type.", "items": { "type": "string", "enum": [ "fulltime", "parttime", "contract", "temporary", "internship" ], "enumTitles": [ "Full-time", "Part-time", "Contract", "Temporary", "Internship" ] }, "default": [] }, "jobRemote": { "title": "Workplace type", "type": "array", "description": "Filter jobs by on-site, remote, or hybrid.", "items": { "type": "string", "enum": [ "onsite", "remote", "hybrid" ], "enumTitles": [ "On-site", "Remote", "Hybrid" ] }, "default": [ "onsite", "remote", "hybrid" ] }, "jobDatePosted": { "title": "Date posted", "enum": [ "any", "month", "week", "3days", "day" ], "type": "string", "description": "Only return jobs posted within this window.", "default": "any" }, "jobSort": { "title": "Sort jobs by", "enum": [ "relevance", "date" ], "type": "string", "description": "Relevance or most recent.", "default": "relevance" }, "jobsPerQuery": { "title": "Jobs per keyword", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum jobs to return per keyword (1–1000).", "default": 25 }, "radiusMiles": { "title": "Search radius (miles)", "minimum": 0, "maximum": 100, "type": "integer", "description": "Radius around the location for job search.", "default": 25 }, "enableCompanyJobs": { "title": "Company jobs", "type": "boolean", "description": "Collect open positions from specific employers on Indeed.", "default": false }, "companyNames": { "title": "Company names", "type": "array", "description": "Employer names as listed on Indeed (e.g. \"Amazon\", \"Target\", \"FedEx\").", "default": [], "items": { "type": "string" } }, "jobsPerCompany": { "title": "Jobs per company", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum jobs to return per company (1–1000).", "default": 25 }, "enableScrapeByUrl": { "title": "Job links", "type": "boolean", "description": "Collect structured data from individual Indeed job page links.", "default": false }, "jobUrls": { "title": "Job URLs", "type": "array", "description": "Indeed job page URLs you want to collect.", "default": [], "items": { "type": "string" } }, "fetchJobDetails": { "title": "Fetch full job details", "type": "boolean", "description": "Include each job's full description, benefits, and applicant count. Slightly slower but much richer.", "default": true }, "includeRaw": { "title": "Include extended data", "type": "boolean", "description": "Attach extended record data under the raw field. Larger output.", "default": false }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "Optional. Every record is always saved to the run's dataset — this webhook is an additional real-time push. When set, each new record is also sent to this URL (CRM, Slack, Zapier, Make, Google Sheets).", "default": "" }, "webhookFormat": { "title": "Webhook format", "enum": [ "json", "slack" ], "type": "string", "description": "json = full record object; slack = Slack-friendly message payload.", "default": "json" }, "country": { "title": "Country", "type": "string", "description": "Target country market (e.g. us, uk, ca, au, de, fr).", "default": "us" }, "maxItems": { "title": "Max total items", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum total job records across all enabled modes.", "default": 10000 }, "proxyConfiguration": { "title": "Proxy settings", "type": "object", "description": "Residential US proxy recommended for best results and consistent throughput.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } } }, "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 } } } } } } } } } } ```