Wellfound Startup Jobs Scraper

Build a clean startup-jobs feed with compensation, equity, remote context, company rollups, and change events.

Scrape Wellfound startup jobs, monitor new/changed/removed listings, and build company hiring snapshots with parsed compensation, equity, remote, role, and company context. No login.

All examples below use fictional DEMO-* identifiers, reserved .test domains, and masked contact details. They do not represent real people, listings, products, or companies.

🚀 What this Actor does

• Flexible collection: scrape, monitor, REMOTE / LOCATION / URLS, jobs / companies / both.
• Structured output: clean JSON records organized into jobs, changes, companies views.
• Production-ready: concurrency, retries, proxy support, limits, and source-aware diagnostics are exposed through the Actor input.
• Easy automation: run from the Apify Console, API, schedules, webhooks, Make, Zapier, or any HTTP client.

🎛️ Modes and workflows

Mode or workflow	What it does
scrape	Collect the current job or company snapshot.
monitor	Label new, changed, and optionally removed jobs against a named state store.
REMOTE / LOCATION / URLS	Choose remote discovery, location searches, or exact Wellfound URLs.
jobs / companies / both	Select detailed jobs, company hiring rollups, or both datasets.

💡 Common use cases

• Startup hiring feeds
• Compensation, equity, and remote-work analysis
• Company hiring snapshots and alerts

📥 Input schema

Configure the Actor in the Input tab or send the same JSON through the API. Fields not needed for your workflow can be omitted.

Field	Type	Description	Default
scrapeMode	string	Choose a one-time scrape or compare this run against previous runs to detect changes. Allowed: scrape, monitor.	scrape
inputMode	string	Choose whether to scrape remote jobs, location names, or your own Wellfound URLs. Allowed: REMOTE, LOCATION, URLS.	REMOTE
outputMode	string	Choose jobs, company hiring summaries, or both. Jobs and company snapshots are saved in separate clean outputs. Allowed: jobs, companies, both.	jobs
urls	array	Use this when Source type is Wellfound URLs. Add location pages, remote pages, role pages, company job pages, or direct job pages.	—
locations	array	Use this when Source type is Location names. Enter city, country, or region names.	[]
pageLimit	integer	Maximum pages to scrape from each source. Use 1 for a fast test. Use 0 to collect all available pages up to the safety limit.	1
maxItems	integer	Maximum records to save across selected outputs. The prefilled value is intentionally small for fast first runs.	1000
onlyRemoteJobs	boolean	Keep only jobs marked as remote.	false
includeChangedJobs	boolean	In monitor mode, save jobs whose title, role, compensation, description, location, remote status, job type, or experience requirements changed.	true
includeRemovedJobs	boolean	In monitor mode, save jobs that disappeared from the monitored source.	true
resetMonitorState	boolean	Clear remembered jobs before this run. Use this when you want to start monitoring from scratch.	false
monitorStateStoreName	string	Named key-value store used to remember jobs between scheduled monitor runs.	wellfound-jobs-monitor-state
maxRetries	integer	Maximum attempts for temporary network or website errors. The default works well for most runs.	5
proxyConfiguration	object	Advanced setting. Leave unchanged for normal Apify runs.	{"useApifyProxy": false}

▶️ Example input

{
  "scrapeMode": "monitor",
  "inputMode": "REMOTE",
  "outputMode": "both",
  "pageLimit": 5,
  "maxItems": 100,
  "monitorStateStoreName": "demo-startup-jobs"
}

📦 Output schema

Each successful item is written to the default dataset. Select a dataset view in the Apify Console or export the full dataset as JSON, CSV, Excel, XML, or RSS.

jobs — Jobs

Normalized job records.

Fields: record_type, event_type, title, company_name, company_logo_url, display_locations, remote, display_compensation, display_posted_at, url, detected_at

changes — Monitor changes

Monitoring events and field-level deltas.

Fields: event_type, changed_fields, title, company_name, compensation, previous_compensation, location_names, previous_location_names, remote, previous_remote, url, detected_at, previous_last_seen_at

companies — Company snapshots

Company-level identity, enrichment, and aggregate signals.

Fields: record_type, company_name, company_logo_url, company_slug, display_company_size, job_count, remote_job_count, role_titles, display_locations, salary_range, display_latest_posted_at, company_url, source_url

📤 Example output

{
  "record_type": "job",
  "event_type": "new",
  "title": "Founding Product Designer",
  "company_name": "Example Startup",
  "display_locations": [
    "Remote"
  ],
  "remote": true,
  "display_compensation": "$110k-$140k + equity",
  "display_posted_at": "1 day ago",
  "url": "https://wellfound.com/jobs/DEMO-WF-JOB-01",
  "detected_at": "2026-08-16T09:00:00Z"
}

Missing source values are returned as null, empty arrays, or documented availability/status fields; the Actor does not invent unavailable source data.

🔌 API example

Replace the placeholder with an Apify token and send the same input used in the Console:

curl -X POST "https://api.apify.com/v2/acts/trakk~wellfound-jobs-scraper/runs?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"scrapeMode": "monitor", "inputMode": "REMOTE", "outputMode": "both", "pageLimit": 5, "maxItems": 100, "monitorStateStoreName": "demo-startup-jobs"}'

For synchronous integrations, use the run-sync-get-dataset-items API endpoint. For larger jobs, start an asynchronous run and consume its default dataset when the run succeeds.

🧩 Automation and exports

• Schedule recurring runs from the Apify Console.
• Trigger downstream systems with webhooks when a run succeeds or fails.
• Reuse named monitoring keys or stores where the selected workflow supports change tracking.
• Export dataset views to JSON, CSV, Excel, XML, or RSS, or access items through the Apify API.

❓ FAQ

Do I need a login or browser session?

Use only the inputs shown in the Actor schema. If authentication or cookies are supported, the relevant encrypted field is explicitly available in the Input tab; otherwise no account is required.

Why can some fields be empty?

Source pages vary by region, content type, privacy settings, and availability. Optional enrichment also depends on the selected mode. Empty values are preserved honestly instead of being guessed.

How should I run this at scale?

Start with a small representative input, inspect the dataset and cost, then raise item limits and concurrency gradually. Use Apify Proxy when the schema exposes it, and use schedules plus monitoring keys for recurring collection.

Is the example data real?

No. Every example in this README is intentionally fictional and uses demo identifiers, reserved domains, or masked contact values.