Head-to-head
Outlier (Scale AI) vs DataAnnotation
Which pays more, which is easier to start, and which fits the work you want. Compared on real pay, work model, payout, and the roles open right now.
Outlier (Scale AI)
DataAnnotationOutlier (Scale AI) vs DataAnnotation: the short answer
On pay, Outlier (Scale AI) is benchmarked at Up to $7–$50/hr; ML, EE and quant finance up to $150/hr and DataAnnotation at $25–$150+/hr; generalists $25–$50/hr; their boards do not state enough rates to tell which pays more, so compare against your own hours.
Both are expert networks, so the barrier to start is similar: gated by a screen for a degree, professional expertise, or a skills test.
Both hire for AI Evaluation, Writing, Coding, Math & STEM, Domain Experts, and Multilingual.
Bottom line: what we know does not separate these two on pay or on how many people they accept, so choose on the specific work each hires for.
| Outlier (Scale AI) | DataAnnotation | |
|---|---|---|
| Typical pay | Up to $7–$50/hr; ML, EE and quant finance up to $150/hr | $25–$150+/hr; generalists $25–$50/hr |
| Work model | Expert network · Expert queue (Scale AI) | Expert network · Assessment-gated contractor |
| Kinds of work | AI Evaluation, Writing, Coding, Math & STEM, Domain Experts, and Multilingual | AI Evaluation, Coding, Math & STEM, Domain Experts, Writing, and Multilingual |
| How you get paid | Weekly (Tuesdays) via PayPal, Airtm or ACH bank transfer. | PayPal; deposits arrive within a few days of a payout request (its FAQ), and its job pages list payouts as weekly (read 2 Nov 2026). |
| Where you can work | Remote, from the places its working guidelines list (effective 15 Jul 2026, read 8 Nov 2026): the US, the UK, India, the Philippines, Brazil and Egypt among them, but not Nigeria, Kenya, Pakistan or Ukraine. English projects dominate, with multilingual projects. | Its FAQ names no country list (it says it connects over 1 million contractors globally) and its job pages say only 'Remote' (both read 2 Nov 2026), but worker reports point to six countries: the US, Canada, the UK, Ireland, Australia and New Zealand (read 18 Oct 2026). |
| Open roles now | See platform | See platform |
| Worker ratings | Trustpilot 3.9/5 (5,781 reviews) (read November 2026) | Trustpilot 3.9/5 (1,978 reviews) (read November 2026) |
Pay shows each platform's live measured band where its feed has enough hourly-stated roles, otherwise our compiled benchmark. How we compile pay.
Best for people with a degree or professional skills who want vetted, higher-skill work.
Best for people with a degree or professional skills who want vetted, higher-skill work.
Some links on AITraining.jobs are referral links. If you sign up through one, AITraining.jobs may earn a commission at no extra cost to you. It never changes what a platform pays you.
Weekly roles email
Get new AI training jobs by email
The newest paid roles across every platform we track, with real hourly pay, in one weekly email. Free, and unsubscribe anytime.
We email new roles, not spam. One click to unsubscribe.
Outlier (Scale AI) vs DataAnnotation: common questions
Which pays more, Outlier (Scale AI) or DataAnnotation?
On pay, Outlier (Scale AI) is benchmarked at Up to $7–$50/hr; ML, EE and quant finance up to $150/hr and DataAnnotation at $25–$150+/hr; generalists $25–$50/hr; their boards do not state enough rates to tell which pays more, so compare against your own hours.
Is Outlier (Scale AI) or DataAnnotation easier to get started with?
Both are expert networks, so the barrier to start is similar: gated by a screen for a degree, professional expertise, or a skills test.
Can you work on both Outlier (Scale AI) and DataAnnotation?
Yes. They are independent platforms, and many contributors join several at once to keep a steady flow of work, especially since both hire for AI Evaluation, Writing, Coding, Math & STEM, Domain Experts, and Multilingual. Signing up for one does not affect the other.
More comparisons
Ordered by what applying to their platforms is worth, lifted by a referral boost for a platform that pays us a referral fee; it never changes what a platform pays you.