Visa Sponsorship Jobs Scraper: Find Postings That Mention Sponsoring Visas

Find job postings whose own text says the employer sponsors visas. You list the company job boards to read (Greenhouse, Lever or Ashby). The actor reads their public job APIs, checks the description of every posting for sponsorship language, and returns one row per posting with a sponsorship signal and the sentence that triggered it.

What does this Actor do?

Many careers pages hide the visa answer deep inside the description. This actor reads that text for you, across as many company boards as you list, and sorts postings into four signals:

• sponsors: the text says the employer sponsors work visas or H-1B for this role.
• no_sponsorship: the text says it does not, or that candidates must work without sponsorship.
• mixed: the posting has both kinds of sentence, for example different rules per country.
• unknown: the posting never mentions sponsorship.

Every flagged row carries evidenceSnippet, the sentence the signal came from, and matchedTerms. You can read the evidence yourself instead of trusting a label.

Run in 30 seconds

1. Open the Actor and press Try for free (a free Apify account is enough).
2. Keep the prefilled boards and press Start. A run takes under a minute.
3. Open the Output tab. Use the table view or download CSV, Excel or JSON.

Input

Field	What it does
companies	List of {"ats": "greenhouse" or "lever" or "ashby", "token": "<board name>"}. The token is the last part of the careers URL.
keywords	Keep postings whose title or department contains one of these words.
locationContains	Keep postings whose location text contains this phrase, for example United States.
postedWithinDays	Keep postings published or updated in the last N days. 0 means no limit.
sponsorshipFilter	sponsors (default), sponsors_or_unknown, or all.
includeDescription	Add the full posting text to every row.
maxItems	Stop after this many postings.

Sample input:

{
  "companies": [
    {"ats": "greenhouse", "token": "anthropic"},
    {"ats": "greenhouse", "token": "verkada"},
    {"ats": "ashby", "token": "openai"}
  ],
  "keywords": ["engineer"],
  "sponsorshipFilter": "sponsors",
  "maxItems": 50
}

To find a board token, open a company careers page and look at the job board link. boards.greenhouse.io/anthropic has the token anthropic. jobs.lever.co/palantir has palantir. jobs.ashbyhq.com/openai has openai.

Output

One row per posting:

Field	Meaning
title, company, department	What the role is and who posted it.
location, remote, employmentType	Where and how, when the board publishes it.
postedAt, updatedAt	ISO dates from the board.
applyUrl	Link to the original posting.
sponsorshipSignal	sponsors, no_sponsorship, mixed or unknown.
evidenceSnippet	The sentence behind the signal.
matchedTerms	The sponsorship terms that matched.
matchedSentenceCount	How many sentences in the posting were about sponsorship.
descriptionText	Full text, only if you turn on includeDescription.
jobId, ats, scrapedAt	Identifiers and run time.

Sample output

{
  "jobId": "4012345",
  "ats": "greenhouse",
  "company": "Verkada",
  "title": "Software Engineer, Backend",
  "location": "San Mateo, CA",
  "sponsorshipSignal": "sponsors",
  "evidenceSnippet": "We do sponsor and take over sponsorship of employment visas for this role.",
  "matchedTerms": ["sponsorship"],
  "matchedSentenceCount": 1,
  "applyUrl": "https://job-boards.greenhouse.io/verkada/jobs/4012345"
}

Use cases

• Build a shortlist of employers that sponsor H-1B or other work visas for your target role.
• Run it weekly on a list of target companies and watch for new sponsoring postings.
• Give recruiters, career coaches or university career centers a sourcing list for international candidates.
• Feed postings and evidence into a spreadsheet, CRM or n8n workflow for follow-up.
• Compare which employers say they do not sponsor, to save applications.

Why use it

• Evidence on every row. You see the sentence, so a wrong call is easy to spot.
• No LLM and no guessing. The classifier is fixed text rules, so results repeat run to run.
• Sentence-level matching. "Executive sponsor" and "sponsored media" do not count. Only sentences about visas, H-1B, or work authorization do.
• Public data only. The actor uses the same job APIs the companies' own careers pages use. No login, no proxy, no personal data.

Pricing

Pay per event. You pay a small fixed amount per posting delivered, listed on the Pricing tab, plus a tiny start fee per run. Postings removed by your filters are never charged, and you can set a maximum cost per run in the run options.

FAQ

How is sponsorship detected? The description is split into sentences. A sentence counts only if it talks about sponsoring a visa or work authorization. If that sentence contains negative wording ("not", "unable", "without"), it is a negative signal, otherwise a positive one. A line like "we cannot sponsor for every role" is treated as positive, because it begins from a yes.

Is this legal or immigration advice? No. It is text matching on public postings. Always confirm with the employer.

Can it find a company I have not listed? No. It reads only the boards you list.

Which boards are supported? Greenhouse, Lever and Ashby. For other applicant tracking systems, see the related Actors below.

Limits

• Only the boards you list are read, and only public postings.
• The classifier can miss unusual wording or misread a sentence. Treat unknown as "no statement found", not as "no".
• Boards publish only their open roles, not an archive.
• Company boards that are renamed or closed return "board not found" in the run log.

Related Actors

• ATS Open Roles reads the open roles of many more applicant tracking systems.
• Workday Jobs Scraper covers companies that post on Workday.
• Remote Jobs Aggregator merges six remote job boards into one deduped dataset.

Found a bug or need a field? Open an issue on the Issues tab with the run URL.

More from DWA Open Data

Browse all 69 data Actors, with live prices and sample output, at open-data-actors.pages.dev.

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