# Remote Jobs API: Match & Score (`dr_amp/remote-jobs-match-api`) Actor Aggregate remote jobs from four public APIs, normalize and deduplicate listings, then rank them against a candidate or hiring profile with explainable scoring. - **URL**: https://apify.com/dr\_amp/remote-jobs-match-api.md - **Developed by:** [Diego Jurado Garcia](https://apify.com/dr_amp) (community) - **Categories:** Jobs, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Remote Jobs API: Match & Score Aggregate current remote-job listings from four public APIs, normalize and deduplicate them, then rank each role against a candidate or hiring profile with explainable deterministic scoring. ### Sources - Arbeitnow - Jobicy - Himalayas - Remote OK No login, browser, paid data provider, or external LLM is required. Each result preserves `source`, `source_url`, `apply_url`, and attribution. Remote OK results link back to Remote OK as required by its public API terms. ### Features - live HTTP fetch with retries for rate limits and transient server/network failures - partial-failure tolerance: one broken feed does not discard the others - normalized title, company, description, location, employment type, salary, currency, skills, seniority, dates, and URLs - cross-source deduplication by canonical URL and normalized title + company - filters for keywords, region, country, employment type, salary floor, and posting age - explainable fit score, fit band, reasons, and data-quality risk notes - one dataset item per unique ranked job - run diagnostics in the `OUTPUT` key-value-store record ### Input example ```json { "platforms": ["arbeitnow", "jobicy", "himalayas", "remoteok"], "search_keywords": "python", "max_jobs_per_platform": 10, "max_total_jobs": 40, "profile": { "desired_roles": ["python engineer", "backend engineer"], "skills": ["python", "django", "postgresql"], "seniority": "senior", "regions": ["europe", "worldwide"], "timezone": "UTC+2", "salary_min": 80000 }, "posted_within_days": 30 } ```` `search_keywords` uses AND semantics after normalization: all words must appear somewhere in the title, company, description, or skills. ### Output Each dataset item includes: - `fit_score`, `fit_band`, `fit_reasons`, `risk_notes` - `title`, `company`, `description`, `location`, `remote_region` - `employment_type`, `salary_min`, `salary_max`, `currency` - `skills`, `seniority`, `published_at` - `apply_url`, `source`, `source_url`, `attribution` Known salary values below `salary_min` are discarded. Listings without salary data are retained and marked in `risk_notes` rather than silently removed. ### Pay-per-event - `run-start`: once per valid run. - `job-scored`: once per unique emitted job. - Discarded, duplicate, or failed-source rows are not charged. ### Local verification ```bash uv run --with-requirements requirements.txt --with pytest python -m pytest tests -q uv run --with-requirements requirements.txt python -m src.main \ --input samples/input.json \ --output /tmp/remote-jobs-output.json apify validate-schema ``` # Actor input Schema ## `platforms` (type: `array`): Public APIs to query. ## `search_keywords` (type: `string`): All words must appear in the normalized title, company, description, or skills. ## `max_jobs_per_platform` (type: `integer`): Maximum normalized matches retained from each selected source. ## `max_total_jobs` (type: `integer`): Maximum ranked jobs emitted after filtering and cross-source deduplication. ## `profile` (type: `object`): Optional scoring profile: desired\_roles, skills, seniority, regions, timezone, salary\_min. ## `region` (type: `string`): Optional region text such as Europe, Americas, Asia, or worldwide. ## `country` (type: `string`): Optional country name matched against normalized location and description. ## `employment_type` (type: `string`): Optional type such as full-time, part-time, contract, or freelance. ## `salary_min` (type: `number`): Jobs without published salary are retained; listings below this known minimum are removed. ## `posted_within_days` (type: `integer`): Discard listings without a parseable date or older than this many days. ## Actor input object example ```json { "platforms": [ "arbeitnow", "jobicy", "himalayas", "remoteok" ], "max_jobs_per_platform": 25, "max_total_jobs": 100, "profile": { "desired_roles": [ "video editor" ], "skills": [ "DaVinci Resolve", "Premiere Pro" ], "seniority": "senior", "regions": [ "europe" ], "timezone": "UTC+2" } } ``` # 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 = { "profile": { "desired_roles": [ "video editor" ], "skills": [ "DaVinci Resolve", "Premiere Pro" ], "seniority": "senior", "regions": [ "europe" ], "timezone": "UTC+2" } }; // Run the Actor and wait for it to finish const run = await client.actor("dr_amp/remote-jobs-match-api").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 = { "profile": { "desired_roles": ["video editor"], "skills": [ "DaVinci Resolve", "Premiere Pro", ], "seniority": "senior", "regions": ["europe"], "timezone": "UTC+2", } } # Run the Actor and wait for it to finish run = client.actor("dr_amp/remote-jobs-match-api").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 '{ "profile": { "desired_roles": [ "video editor" ], "skills": [ "DaVinci Resolve", "Premiere Pro" ], "seniority": "senior", "regions": [ "europe" ], "timezone": "UTC+2" } }' | apify call dr_amp/remote-jobs-match-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dr_amp/remote-jobs-match-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Remote Jobs API: Match & Score", "description": "Aggregate remote jobs from four public APIs, normalize and deduplicate listings, then rank them against a candidate or hiring profile with explainable scoring.", "version": "0.1", "x-build-id": "xQfA1zTjMtD2HOdzn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dr_amp~remote-jobs-match-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dr_amp-remote-jobs-match-api", "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/dr_amp~remote-jobs-match-api/runs": { "post": { "operationId": "runs-sync-dr_amp-remote-jobs-match-api", "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/dr_amp~remote-jobs-match-api/run-sync": { "post": { "operationId": "run-sync-dr_amp-remote-jobs-match-api", "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": { "platforms": { "title": "Job sources", "type": "array", "description": "Public APIs to query.", "items": { "type": "string", "enum": [ "arbeitnow", "jobicy", "himalayas", "remoteok" ], "enumTitles": [ "Arbeitnow", "Jobicy", "Himalayas", "Remote OK" ] }, "default": [ "arbeitnow", "jobicy", "himalayas", "remoteok" ] }, "search_keywords": { "title": "Search keywords", "type": "string", "description": "All words must appear in the normalized title, company, description, or skills." }, "max_jobs_per_platform": { "title": "Maximum jobs per source", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum normalized matches retained from each selected source.", "default": 25 }, "max_total_jobs": { "title": "Maximum total results", "minimum": 1, "maximum": 400, "type": "integer", "description": "Maximum ranked jobs emitted after filtering and cross-source deduplication.", "default": 100 }, "profile": { "title": "Matching profile", "type": "object", "description": "Optional scoring profile: desired_roles, skills, seniority, regions, timezone, salary_min." }, "region": { "title": "Remote region filter", "type": "string", "description": "Optional region text such as Europe, Americas, Asia, or worldwide." }, "country": { "title": "Country filter", "type": "string", "description": "Optional country name matched against normalized location and description." }, "employment_type": { "title": "Employment type filter", "type": "string", "description": "Optional type such as full-time, part-time, contract, or freelance." }, "salary_min": { "title": "Minimum listed salary", "type": "number", "description": "Jobs without published salary are retained; listings below this known minimum are removed." }, "posted_within_days": { "title": "Posted within days", "minimum": 1, "maximum": 365, "type": "integer", "description": "Discard listings without a parseable date or older than this many days." } } }, "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 } } } } } } } } } } ```