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Research report ยท October 2026 edition

What Raises AI Training Pay

Not enough priced roles on 31 Oct 2026 to compare pay within kinds of work.

Read the month's story: The AI Training Job Market in October 2026

Data window
1 Oct 2026 to 31 Oct 2026
31 days, UTC
Frozen
11 Nov 2026, 14:34 UTC
These figures will not change
Source
The public job boards of the AI training platforms this site tracks, read every hour. Descriptions come from the platforms whose boards publish them in full.
Method
Version 3. Definitions
CC BY 4.0, how to cite

Every figure on this page as CSV and JSON, sent to your work email.

Key findings

There is not enough data in this window to state findings.

Figure 1

Pay premiums, compared within each kind of work

Which traits of a role come with higher advertised pay, all else in its kind of work equal?

TraitPremium within kindMedian withMedian without
Assessment or test in the descriptionSmall sample
n/a
n/an/a
Professional credential in the descriptionSmall sample
n/a
n/an/a
Title names an expert fieldSmall sample
n/a
n/an/a
Title names a languageSmall sample
n/a
n/an/a
PhD in the descriptionSmall sample
n/a
n/an/a
Senior, staff, principal or lead titleSmall sample
n/a
n/an/a
Open only to US residentsSmall sample
n/a
n/an/a

Sample. Roles open on 31 Oct 2026 that state an hourly rate. The last three traits compare the 0 open roles whose platform publishes a full description ().

Premium within kind: for each kind of work with at least 3 priced roles on both sides, the median rate with the trait over the median without it, minus one; then the average across those kinds, weighted by the roles with the trait. The medians with and without are across all kinds, for context: where they disagree with the premium, the trait is concentrated in better or worse paid kinds of work.

A premium is an association in advertised pay, not a cause: traits travel together (a credentialed role is often also senior).

Source. AITraining.jobs Research, What Raises AI Training Pay, October 2026 edition.

Figure 2

Naming an expert field, kind by kind

Does a title that names a profession pay more within each kind of work?

No data in this window.

Sample. Roles whose title names a profession or discipline, against roles whose title names none, open on 31 Oct 2026; kinds of work with at least 3 priced roles on both sides.

Each median rests on at least 3 priced roles (the one minimum of every median: the fewest whose span holds the true middle more likely than not), and the counts behind each are shown: a median of a few roles moves with a few postings.

Source. AITraining.jobs Research, What Raises AI Training Pay, October 2026 edition.

Figure 3

Naming a language, kind by kind

Do roles for a named language pay more or less than other roles of the same kind?

No data in this window.

Sample. Roles whose title names a language, against roles whose title names none, open on 31 Oct 2026; kinds of work with at least 3 priced roles on both sides.

Each median rests on at least 3 priced roles (the one minimum of every median: the fewest whose span holds the true middle more likely than not), and the counts behind each are shown: a median of a few roles moves with a few postings.

Source. AITraining.jobs Research, What Raises AI Training Pay, October 2026 edition.

Figure 4

The US-only premium, kind by kind

Do roles open only to US residents pay more than roles open worldwide, within each kind of work?

No data in this window.

Sample. Roles open only to US residents, against roles open worldwide, open on 31 Oct 2026; kinds of work with at least 3 priced roles on both sides.

Each median rests on at least 3 priced roles (the one minimum of every median: the fewest whose span holds the true middle more likely than not), and the counts behind each are shown: a median of a few roles moves with a few postings.

Source. AITraining.jobs Research, What Raises AI Training Pay, October 2026 edition.

For labs, data vendors and researchers

Buy the data behind this report

The figures above are a summary. Behind them are records we collect ourselves, every day:

  • 0 roles tracked, each with its history

    Every role on 0 job boards, read since n/a (every hour since 18 Oct 2026): its pay and place, and the first and last day it was open.

  • 0 apply clicks in 28 days

    Which roles people actually apply to, by field, pay and kind of work. It happens on this site, so nobody else can count it.

  • 39 lab and vendor hiring boards

    The job boards of 25 AI labs and 14 human-data vendors, read every day: who is hiring for human data, and who is hiring to buy it.

What you can buy

  • The records

    The rows behind any figure, with their history, not only the totals.

  • A regular feed

    The same figures every week or month, as files.

  • A custom cut or benchmark

    Your countries, languages or fields, or your own platform against the market.

Building AI and need the experts behind this data? (you contract them yourself) or (we deliver the expert work).

Investing in AI-data companies? Hiring radar is these records role by role, every day, as files.

Method and definitions

The public job boards of the AI training platforms this site tracks, read every hour. Descriptions come from the platforms whose boards publish them in full. Every figure is computed by one database query over the window shown, the same query for the live report and for every edition. Each figure states its sample beneath it.

Premium within kind
For each kind of work with at least 3 roles stating an hourly rate on both sides (the one minimum of every median), the median rate with the trait over the median without it, minus one; averaged across those kinds, weighted by the roles with the trait. A trait needs two such kinds of work to show a premium.
Expert field, language
Named in the title, matched as whole words against the same vocabularies as the expert-fields and languages reports.
Professional credential
A description naming a medical, law, finance or nursing qualification, a board certification or a licence, read with the patterns published in the requirements report.
US-only
A role whose location rule names the United States and no other country, compared with roles open worldwide.
Advertised pay
The hourly figure a posting states (the middle of a stated range), counted once per distinct rate as the job board counts it. The median and typical pay are the board's: typical pay runs from the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling, stated from 3 distinct rates.
Kind of work
Each role is classified from its title and description into one of the twelve kinds of AI training work this site tracks, from AI evaluation and coding to multilingual and audio work. Every kind links to its own page.
Open role
A role listed by a given day and still in its platform's feed that day.

What this data cannot tell you

  • Platforms that recruit without a public job board are not counted. Several large ones invite workers to projects directly.
  • A listing is not a hire. Some platforms keep evergreen roles open for months, and some post one listing per language or country.
  • A premium is an association in advertised pay, not a cause: traits travel together, and the comparison holds only the kind of work fixed.
  • Descriptions are published by a few platforms only, so the credential, PhD and assessment premiums describe those platforms.
  • Pay is what postings advertise, not what workers are paid after bonuses, tiers or rejected tasks.

How the job feeds are read and roles are classified: site methodology. How fresh, complete and consistent the data is, checked every day: data quality and coverage.

Editions

The live report covers the last 28 complete days and changes every day. Each complete month is also published as an edition, frozen two days after the month ends, so a figure you cite from an edition never moves.

  • Live dataLast 28 complete days, recomputed daily
  • October 2026 edition (this page)Frozen 11 Nov 2026

Cite and reuse

Free to quote, chart and republish under CC BY 4.0 (creativecommons.org/licenses/by/4.0) with a link to this page. This edition is frozen, so its figures will read the same later.

Citation

AITraining.jobs (2026). What Raises AI Training Pay, October 2026 edition. https://cyberjobs.cc/research/ai-training-pay-premiums/2026-10

BibTeX

@misc{aitrainingjobs_ai_training_pay_premiums_2026_10,
  author = {{AITraining.jobs}},
  title = {What Raises AI Training Pay, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://cyberjobs.cc/research/ai-training-pay-premiums/2026-10}},
}
Data: every figure as CSV (one line per value) and JSON, sent to your work email.Pay and open-roles data

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