Wellfound Startup Jobs Scraper

Scrape startup job listings from Wellfound.com (formerly AngelList Talent) — title, compensation band, locations, remote flag, posted date, plus the startup's name, logo, slug, company-size band, market tags, headcount, and Wellfound's funding-stage / top-investor / recently-funded / growing-fast signals — denormalized into every row. Paste any /jobs listing URL (with optional ?location, ?industry, or ?market filter) and get back self-contained flat rows ready for CSV.

Why this actor

Wellfound is the largest English-language startup job board — ~50 jobs per listing page across many filters and ~500 pages of pagination. It also runs DataDome anti-bot protection on company-profile, role-search, and individual-job-detail pages, so most scrapers either break or charge premium prices for thin data.

This actor takes a different angle: everything you need is already on the listing page. Wellfound server-renders its /jobs Apollo state with the full JobListing + Startup graph embedded — one fetch unlocks ~50 jobs with denormalized company data, no detail-page enrichment required.

• Three-stack race fetch — impit (Rust + rustls Firefox), gotScraping (Node + headerGenerator), and impers (libcurl-impersonate Chrome 142). The fastest legit response wins per page, so a single fingerprint hiccup doesn't burn the retry budget
• Apollo-state extraction — one JSON.parse of __NEXT_DATA__ resolves JobListing → Startup → Badge / NewTag / JobListingRemoteConfig refs in-memory. No DOM walking
• Per-URL maxItems — paste 3 listing filters with maxItems: 200 → up to 600 rows (200 per filter). Free-tier users have a hidden global ceiling of 100 rows
• Apify Residential US by default — Wellfound is US-centric and serves canonical English pages with full Apollo state on US exits
• One flat row per job — company-level fields are denormalized on every row so CSV consumers don't need to join
• No actor-start fee — pricing is a flat $0.0015 per row ($1.50 / 1,000 jobs). Your cost = rows × rate, with nothing extra on top. Most Wellfound scrapers add a per-run charge ($0.005-$0.20) on top of their per-row rate; we don't

v1.1 — opt-in /company/{slug} enrichment 🆕

When you set enrichCompanyProfile: true, after the listings phase completes the actor runs a second pass: for each unique startup in the dataset, it fires 30 parallel undici fetches at /company/{slug}, parses the Apollo state, and merges these fields into every job row for that company:

Field	What it carries	Example (Airbnb)
companyTotalRaised	Total funding amount in USD (integer)	11333560000 ($11.3 B)
companyFundingRoundsCount	Number of recorded rounds	20
companyLatestRoundType	Most recent round name	"IPO"
companyLatestRoundClosedAt	ISO timestamp of latest round	"2020-11-27T..."
companyFundingRounds[]	Full round history (roundType, closedAt, valuation)	20 rounds back to Series B 2011
companyProductDescription	Long-form product/company bio	Full Airbnb marketing copy
companyWebsiteUrl	Official company URL (not Wellfound)	"http://airbnb.com"
companyTwitterUrl / companyLinkedinUrl / companyFacebookUrl / companyBlogUrl / companyProductHuntUrl	All social URLs	Populated when present
companyIsOperating	Whether Wellfound flags it as operational	true
companyIsIncubator	Whether the profile is an incubator	false
companyIsShell	Wellfound's shell-company flag	false
companyIsYcFunded	Y Combinator funding (new on /company/, not exposed on listings!)	true
companyProfileCompletenessScore	Wellfound's internal 0-100 completeness	78
companyFounders[]	Founder identities resolved from User refs	[{name: "Joe Gebbia", slug: "joegebbia", ...}, {name: "Brian Chesky", ...}]
enrichmentStatus	'enriched' / 'failed' / null	—
enrichmentAttempts	How many fetch attempts the burst used	7

Bonus — per-job "side-band" data (free side-effect of company enrichment)

The /company/{slug} Apollo state embeds the company's recent JobListings with richer fields than the listing-page versions. When company enrichment succeeds, the embedded data is harvested for free and populated on the matching job rows — no extra fetches, no extra charges, no DataDome wall to cross:

Field	Description	Coverage example (Airbnb)
jobDescriptionSnippet	First ~500 chars of the job description as HTML (the "snippet" Wellfound shows in cards). Partial answer to "full job description" without /jobs/{id}.	10/10 jobs populated
jobType	"full_time" / "contract" / "part_time" / "internship"	10/10
equity	Equity component separately from compensation (e.g. "0.1% – 0.5%")	0/10 (Airbnb's public, no equity offered)
yearsExperienceMin / yearsExperienceMax	Required experience range	10/10
autoPosted	true if the job is auto-syndicated from an ATS	10/10 (Airbnb is auto-posted)
atsSource	Original ATS source ("greenhouse" / "lever" / etc.) when syndicated	0/10 (Airbnb returns null)
recruitingContact	Hiring-manager identity when Wellfound exposes it — { name, slug, avatarUrl, pathName }. Typically populated for manually-posted jobs at smaller startups, null for auto-posted ATS jobs.	0/10 (Airbnb is ATS-auto-posted)

Pricing

Event	When charged	Rate
additional-data	Every job row written	$0.0015 ($1.50 / 1k rows)
company-enrichment	Per successful company (de-duped — a company with 56 jobs = 1 charge)	$0.0015 per company

So a 1,000-row run with enrichment ON across ~150 unique companies costs roughly $1.50 (rows) + $0.225 (companies) = $1.725. Failed enrichments cost nothing extra.

Honest caveats

• Best-effort fetching. Wellfound's DataDome wall on /company/ lets a fluctuating 5-15% of attempts through per IP-session. With 30 parallel attempts per company we typically hit 70-90% URL success rate — but in observed pool-degraded windows we've seen 0%. Every row carries enrichmentStatus so you always know which got through.
• enrichJobDetail is the harder surface. Wellfound's job-detail pages are protected more aggressively than company pages — expect ~30-60% per-job success on a good day, lower during anti-bot surges. Failed enrichments are NOT charged.

---

Honest field-coverage note

Wellfound only attaches the full structured graph to featured listings (~4 of ~50 jobs per page). The remaining ~92% of rows carry the basic job + company-identity fields (title, comp band, locations, remote, posted, company name + slug + logo) but leave the funding-stage / market-tags / badges / company-size fields as null / empty arrays.

What this means for you:

Always populated (every row)	Sparse — only on featured rows (~8%)
jobId, jobTitle, jobUrl, jobSlug	companySize, companySizeBand
compensation + parsed min/max/currency/equity	companyHighConcept
locations[], remote, remoteKind, wfhFlexible	liveJobListingsCount
primaryRoleSlug, postedAt, postedAtUnix	marketTags[], locationTags[]
companyId, companyName, companySlug, companyUrl, companyLogoUrl	companyStage, companyStageLabel
recentlyFunded, hasTopInvestors, growingFast, activelyHiring, topResponder, quickResponder (default false for non-featured)	businessType (B2B / B2C)
	allBadgeLabels[]

To get only the rich-featured rows, filter your output for companyStage != null post-run. Across multiple pages the featured set rotates, so paginating to ?page=N reveals progressively more featured startups.

Use cases

• Startup hiring tracker — paginate /jobs?market=ai daily to track which AI startups are hiring fastest, what salary bands they advertise, and which companies hit Wellfound's GROWING_FAST or RECENTLY_FUNDED flags
• Sourcer / recruiter tooling — feed companySlug + companyName into outbound CRMs to build a "currently hiring in {market}" lead list; the compensation band on every row lets you pre-filter by salary tier
• Compensation benchmarking — compensationMin / compensationMax / compensationCurrency / hasEquity are parsed from Wellfound's raw band strings, so you can run quantile analysis without re-parsing
• VC / analyst feeds — featured-row signals (companyStage, recentlyFunded, hasTopInvestors, growingFast) are useful for tracking which startups Wellfound itself flags as venture-backed and growing. Honest caveat: investor names + raise amounts aren't published on the listing surface, only the boolean flags
• Remote-job aggregation — remote: true + acceptedRemoteLocations[] lets you filter for region-eligible remote roles

Input

Field	Type	Required	Notes
startUrls	string[]	yes	Wellfound /jobs listing URLs (optionally with ?location, ?industry, ?market, ?page params). Detail URLs (/jobs/{id}, /company/{slug}, /role/...) are rejected — DataDome blocks them for HTTP-only clients.
maxItems	integer	no	Maximum job rows emitted per startUrl. 3 listings × maxItems: 200 → up to 600 total rows (200 each). Each row = one paid additional-data. Default 1000. Free-tier users have a hidden global ceiling of 100 rows.
maxConcurrency	integer	no	Parallel HTTP requests across listing URLs. Sweet spot 3–5 via Apify Residential US. Default 4.
maxRequestRetries	integer	no	Per-URL retry budget. Each retry rotates the proxy session with mild exponential backoff and re-races the three HTTP stacks. Default 10.
proxy	object	no	Apify Residential US is the default. Direct connections from non-US IPs sometimes get rerouted to localized variants; US residential always returns canonical English pages.

Example input

{
  "startUrls": [
    "https://wellfound.com/jobs",
    "https://wellfound.com/jobs?market=ai",
    "https://wellfound.com/jobs?location=san-francisco"
  ],
  "maxItems": 200,
  "maxConcurrency": 4,
  "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" }
}

That yields up to 600 job rows — 200 per listing URL, ~4 pages each (Wellfound serves ~50 jobs per page).

Output schema

One flat row per JobListing. All identity + compensation + remote + posted fields are populated on every row; the structured "featured" fields are sparse (see honest note above).

{
  // ── Job identity ──
  "jobId":           "4246042",
  "jobUrl":          "https://wellfound.com/jobs/4246042-sales-development-representative",
  "jobSlug":         "sales-development-representative",
  "jobTitle":        "Sales Development Representative",

  // ── Compensation (parsed best-effort from Wellfound's free-text band) ──
  "compensation":         "$40k – $80k • No equity",
  "compensationMin":      40000,
  "compensationMax":      80000,
  "compensationCurrency": "USD",
  "hasEquity":            false,

  // ── Location + remote ──
  "locations":               ["Dubai", "New York City", "San Francisco", "London", "Paris", "Bengaluru"],
  "acceptedRemoteLocations": [],
  "remote":                  true,
  "remoteKind":              "REMOTE",       // REMOTE / ONSITE / HYBRID
  "wfhFlexible":             false,

  // ── Role + time ──
  "primaryRoleSlug":  "sales-development-3",
  "postedAt":         "2026-05-22T06:49:02.000Z",
  "postedAtUnix":     1779432542,

  // ── Company identity (denormalized — always populated) ──
  "companyId":         "10559109",
  "companyName":       "CredShields Technologies",
  "companySlug":       "credshields-blockchain-security",
  "companyUrl":        "https://wellfound.com/company/credshields-blockchain-security",
  "companyLogoUrl":    "https://photos.wellfound.com/startups/i/10559109-….jpg",

  // ── Company structured data (FEATURED ROWS ONLY — ~8% of rows have these) ──
  "companySize":           "SIZE_201_500",       // null on non-featured rows
  "companySizeBand":       "201-500 employees",   // null on non-featured rows
  "companyHighConcept":    "Unlock the potential of every investment partnership",  // null on non-featured rows
  "liveJobListingsCount":  56,                    // null on non-featured rows — total open jobs at this company
  "marketTags":            ["Real Estate Tech", "B2B Software"],   // [] on non-featured rows
  "locationTags":          ["San Francisco"],     // [] on non-featured rows

  // ── Wellfound badge signals (FEATURED ROWS ONLY) ──
  "companyStage":      "scale_stage",        // "early_stage" / "scale_stage" / null
  "companyStageLabel": "Scale Stage",         // human label / null
  "recentlyFunded":    false,                  // raised in last 6 months (boolean)
  "hasTopInvestors":   true,                   // Wellfound flagged top investors (boolean)
  "growingFast":       true,                   // strong hiring growth in last month (boolean)
  "activelyHiring":    true,                   // actively processing applications (boolean)
  "topResponder":      false,                  // top 1% of responders (boolean)
  "quickResponder":    false,                  // responds within a day (boolean)
  "businessType":      "B2B",                  // "B2B" / "B2C" / null
  "allBadgeLabels":    ["Actively Hiring", "B2B", "Scale Stage", "Top Investors", "Growing fast"],

  // ── Meta ──
  "sourcePageUrl":    "https://wellfound.com/jobs",
  "sourcePageIndex":  1,
  "scrapedAt":        "2026-05-22T09:13:58.526Z"
}

Key output fields

• jobId + jobUrl — stable Wellfound identifiers. jobUrl is the canonical permalink; useful as a join key even though Wellfound itself blocks HTTP fetches of the URL
• compensation parsed band — compensationMin / compensationMax come from Wellfound's free-text strings via a best-effort regex. null when Wellfound shows "Competitive" or omits a band entirely
• remote + remoteKind + wfhFlexible — three flags so you can distinguish "fully remote", "on-site with WFH flexibility", and "hybrid"
• postedAt ISO + postedAtUnix — the moment Wellfound first published the listing (liveStartAt in their schema)
• Company "rich" fields — only populated on featured rows. The honest note above explains why — Wellfound only attaches the structured graph to paid-promoted listings, and we report what Wellfound actually serves rather than padding non-featured rows with fake data

How it works

1. Resolve & dedupe the startUrls — accept /jobs[?…] listing URLs; reject detail URLs up-front with a clear reason
2. Race three HTTP stacks (impit Firefox / gotScraping / impers Chrome 142) against the first page; first 200 OK with a real body (~250 KB) wins
3. Parse __NEXT_DATA__ — one JSON.parse resolves the full Apollo normalized graph (JobListing, Startup, Badge, NewTag, JobListingRemoteConfig)
4. Walk JobListing entries in document order, resolve refs in-memory, emit one flat row per job with denormalized company data
5. Paginate to ?page=N+1 until either the parser returns 0 rows or per-URL maxItems is hit
6. Push each row through Dataset.pushData + Actor.chargeOutputRecord('additional-data')

FAQ

Why are the company-size / market-tag / badge fields empty on most rows? Wellfound only attaches the full Apollo Startup payload to featured (paid-promoted) listings — roughly 4 of every 50 jobs per page. Non-featured rows get the lean shape (id, name, slug, logoUrl). We surface the truth of what Wellfound serves; we don't fabricate data. To get only the rich rows, filter your dataset post-run for companyStage != null.

Can you scrape the full job description / company profile / investor list? No — those live behind DataDome-protected detail pages (/jobs/{id}, /company/{slug}) that don't serve to non-browser clients. Adding a JS-runtime stack would bypass this but would also dramatically raise per-row cost and break the listings-only price point. We chose to ship narrow + honest.

Is the actor US-only? The default proxy is US Residential because Wellfound is US-centric and US exits return canonical English pages. EU residential also works; the proxy is configurable.

Does pagination really go to page 500? Yes — we verified /jobs?page=500 returns 200 OK with full Apollo state. The realistic ceiling is wherever Wellfound stops serving fresh listings; the scraper's natural stop condition is "0 rows on a page → end".

What happens if Wellfound changes the Apollo schema? The parser emits a structured warning (apolloState.data missing or malformed) and the page is treated as the end of pagination — noisy degradation rather than silent breakage. You'll see the warning in the log immediately on the first run.

How do I get only fully-remote jobs? Filter the output for remote === true. We can't push the ?remote=true query filter to Wellfound directly — DataDome blocks that specific param — so we filter client-side after the scrape.

Support

Issues / feature requests / pricing questions — open a ticket on the Apify console issues tab for this actor.

Additional services

Apify hosts a portfolio of complementary actors covering related surfaces. If you need scrapers for LinkedIn jobs, Indeed, Glassdoor reviews, or AmbitionBox employee feedback, check the same author's other listings.

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⚠️ Disclaimer

This actor scrapes only publicly accessible Wellfound listing pages (https://wellfound.com/jobs). It does not bypass authentication, solve CAPTCHAs, or access private data. Detail URLs (/jobs/{id}, /company/{slug}, /role/...) are explicitly rejected — we don't try to fetch DataDome-protected surfaces. You are responsible for compliance with Wellfound's Terms of Service in your jurisdiction. The scraper is provided "as is" without warranty; use is at your own risk.

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