AI & ML Engineer Jobs Scraper — 8 Boards in One

One call, eight sources, one bill. This AI/ML jobs aggregator runs 8 job-board scrapers tuned for AI/ML roles inside a single Actor, merges and dedupes into one dataset, and normalizes structured salary, remote flag and seniority uniformly across every board.

What machine learning jobs data does this scraper extract?

Each result is one flat JSON record per job posting. The same structured columns are filled for every source (from whichever field that source exposes), so you never have to special-case per board:

Field	Type	Meaning
source	string	Which child board the record came from, e.g. "ai_jobs_net"
id	string	Stable source-side identifier ("" when the source has none)
title	string	Job title as posted
company	string	Hiring company / organisation
location	string	Location / duty station (may include remote hints)
url	string	Direct link to the posting (primary dedupe / delta key)
postedAt	string	Posting date where the source provides it, else ""
snippet	string	Short description excerpt
description	string	Full description text where the source exposes one, else ""
salary	string	Human-readable salary text, or composed from the numbers below
salaryMin	number | null	Lower bound of the pay range as a number
salaryMax	number | null	Upper bound of the pay range as a number
salaryCurrency	string | null	Currency code (USD, EUR, GBP, PLN, …)
salaryPeriod	string | null	Pay period, one of year/month/week/day/hour
isRemote	boolean | null	true only for fully-remote, false for hybrid/on-site, null if unknown
remoteType	string | null	remote / hybrid / on-site (keeps the hybrid nuance)
seniority	string | null	Experience level, e.g. "Senior", "Mid-Senior level"
employmentType	string | null	Commitment / contract type, e.g. "Full-time", "Contract"

Structured salary and the remote/seniority/type fields are populated from each source's own structured data where available: ai_jobs_net, builtin, remote_boards, wttj and justjoinit expose salaryMin/Max/Currency/Period directly; for ycombinator_was and hackernews the bundle parses the numbers out of the free-text pay line when the poster includes one. linkedin doesn't quote pay on its listings, so its salary fields stay empty/null; a hackernews post that names no figure is left null too. Any field a source doesn't provide is "" (strings) or null (numbers/booleans) rather than fabricated.

How the bundle works

This is a bundle Actor: one endpoint that runs every job-board scraper listed below in-process — their code ships inside this Actor, so no child actor runs are launched and no per-source fees stack on top. You pay this bundle's pay-per-event pricing only. Sources run concurrently, every record is mapped onto one flat schema with salary/remote/seniority normalized uniformly, and results are deduped by URL across boards. You can restrict the run to a subset with the sources input. Each source fails open independently: if one board errors or times out, the others still return.

Delta mode — only new jobs since last run

Turn on onlyNewSinceLastRun for a scheduled alert bot. The bundle remembers every listing URL it has delivered (in a private key-value store on your own Apify account) and, on later runs, drops — and does not charge its per-result fee for — anything you already received. The first run returns everything; subsequent runs surface only fresh roles. Leave it off for a full snapshot each run.

How to scrape machine learning jobs with this Actor

1. Click Try for free / Run — no login to the target site, no cookies, no proxies to configure.
2. Adjust the input (keyword, filters, maxItems) or keep the defaults.
3. Run it and export the dataset as JSON, CSV or Excel, or read it over the API.

Run it from your own code:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("nomad-agent/ml-ai-dev-bundle").call(run_input={"maxItems": 50})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], "—", item["company"], item["url"])

Or a single HTTP call that runs the Actor and returns items in one response:

curl -X POST \
  "https://api.apify.com/v2/acts/nomad-agent~ml-ai-dev-bundle/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"maxItems": 50}'

Input

Field	Type	Default	Notes
sources	array	["linkedin", "ai_jobs_net", "hackernews", "ycombinator_was", "builtin", "remote_boards", "wttj", "justjoinit"]	Which boards to include. Leave empty to run the full default set. All sources run in-process — no per-source fees.
keyword	string	""	Optional free-text filter forwarded to sources that support it (others ignore it).
onlyNewSinceLastRun	boolean	false	Delta mode — return (and bill) only listings not delivered on a previous run with this flag on. See "Delta mode" above.
maxItemsPerSource	integer	36	Cap on items fetched from EACH board before merge.
maxItems	integer	288	Hard cap on the merged, deduped output. Default is sources × maxItemsPerSource (the zero-config ceiling). Set 0 for no cap.
cacheTtlSeconds	integer	1800	How long to reuse results already fetched from a source instead of re-fetching. 0 = always fetch fresh.
concurrency	integer	6	How many boards to fetch in parallel. (Advanced)
runTimeoutSecs	integer	240	How long to give each source before returning what it has collected so far. Sources run in parallel, so this is a per-source ceiling, not a budget shared across them. (Advanced)
apifyToken	string (secret)	""	Leave empty — injected automatically on the Apify platform. Only set for local runs outside the platform. (Advanced)

Output example

{
  "source": "ai_jobs_net",
  "id": "200475",
  "title": "Machine Learning Engineer",
  "company": "Hugging Face",
  "location": "Remote",
  "url": "https://aijobs.net/job/machine-learning-engineer-remote-200475/",
  "postedAt": "2026-06-28",
  "snippet": "We're hiring an ML engineer to work on...",
  "description": "We're hiring an ML engineer to work on our open-source model tooling. You will...",
  "salary": "$140,000–$200,000/yr",
  "salaryMin": 140000,
  "salaryMax": 200000,
  "salaryCurrency": "USD",
  "salaryPeriod": "year",
  "isRemote": true,
  "remoteType": "remote",
  "seniority": "Senior",
  "employmentType": "Full-time"
}

Every record from every board has this same shape. Fields the source doesn't provide come back as "" (strings) or null (numbers/booleans) — e.g. linkedin and hackernews rows have empty salary fields.

Pricing

Pay per event: $0.01 per Actor start and $0.003 per job returned ($3 per 1,000 jobs). That is the whole bill — every source runs inside this Actor, so there are no child-actor fees on top.

Zero-config run estimate (defaults, all 8 sources): up to ~288 merged items for roughly $0.88 all-in ($0.01 start + 288 × $0.003). Real runs usually cost less — not every board returns the full cap, cross-board duplicates are billed once, and delta mode never re-bills a listing you already received.

Use cases

• AI-specialist job boards
• ML-engineer alert bots
• AI-talent market research
• Recruiting pipelines for data/ML teams

FAQ

Is it legal to scrape machine learning jobs? This Actor reads only publicly available job postings — data any visitor can see without logging in. No personal data behind authentication is touched. Review the target site's terms and your local regulations for your specific use case.

Do I need an account on the target site? No. Postings are fetched from public pages/APIs — no login, cookies or session tokens.

How fresh is the data? Every run fetches live listings. Results are cached for cacheTtlSeconds (default 30 min, set 0 to always hit the source live).

How many jobs can I get? maxItems caps the run (set 0 for no cap). Most sources paginate from newest to oldest.

Something broken or missing? Open an issue on the Actor's Issues tab — it is monitored and reliability fixes ship fast.

Integrations

Export the dataset as JSON, CSV or Excel, or read it straight from the Apify API. Works out of the box with Make, Zapier and n8n via their Apify integrations, can be called synchronously with run-sync-get-dataset-items from any backend, and is usable by AI agents through the Apify MCP server.

Is this Actor useful to you? A quick ⭐ review on the Actor's Reviews tab helps other AI/ML and developer job seekers find it — and tells us what to build next.

Related Actors

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• Hacker News Who Is Hiring Scraper — HN Jobs
• Y Combinator Jobs Scraper — Work at a Startup
• Built In Jobs Scraper — US Tech & Startup Jobs
• Remote Jobs Scraper — RemoteOK Remotive WWR
• Welcome to the Jungle Jobs Scraper (WTTJ)
• JustJoin.it Jobs Scraper — Polish Tech & IT Jobs

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