Key findings

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

Figure 1

What this report can see, platform by platform

For which platforms can screening be read, and from which source?

Platform	Open roles	Full descriptions read	Application forms read	Screening read from
All platforms	0	n/a	n/a	0 of 0 platforms read

Sample. The 0 roles open on 31 Oct 2026 on the 0 platforms AITraining.jobs reads; full descriptions of 0 of them and application forms of 0.

Shares are of each platform's own open roles. A platform's board either publishes full descriptions or exposes its application form through an applicant-tracking system, and some do neither: each later figure ranks a platform only on the source it publishes.

Descriptions and forms are read on the same day as the open roles.

No row with any open roles is a small sample: the rows differ so much that each reads on its own from its first.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 2

Screening steps stated in role descriptions

How often do platforms say they will test, interview or verify an applicant, or ask for proof of expertise?

Step	Roles stating it	Share of described roles	Platforms stating it (of 0)
An assessment, test or trial taskSmall sample	0	n/a	0
An AI-led or recorded interviewSmall sample	0	n/a	0
An interview with a person, or of an unstated kindSmall sample	0	n/a	0
A background checkSmall sample	0	n/a	0
Identity verificationSmall sample	0	n/a	0
A professional credential or licence namedSmall sample	0	n/a	0
Work samples, a portfolio or publicationsSmall sample	0	n/a	0

Sample. 0 roles open on 31 Oct 2026 whose job board publishes a full description (none): n/a of the 0 roles open on the 0 platforms read.

A step counts when the description states it, as a requirement or as something that may be asked ('a brief assessment may be added'). A platform can screen more than it writes down, so every share is a floor.

The assessment, interview and check steps are read only in the passage about applying and selection (a selection section, or a sentence that speaks of applicants, candidates, onboarding or the hiring process), so 'conduct psychological assessments' or 'transcribe interviews' in the work itself is not counted. The requirements report counts any mention, so its shares are higher.

An AI-led or recorded interview has its own line; a role that also states a further interview ('an AI interview ... and an interview with a recruiter') counts on both. A credential or licence, and work samples, a portfolio or a publication record, are proof of expertise and are read from the whole description: named as a requirement or a preference.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 3

Screening depth: steps stated per role

How many screening steps does a typical AI training role describe?

Steps stated	Roles	Share of described roles
None statedSmall sample	0	n/a
1 stepSmall sample	0	n/a
2 stepsSmall sample	0	n/a
3 steps or moreSmall sample	0	n/a

Sample. 0 roles open on 31 Oct 2026 whose job board publishes a full description (none): n/a of the 0 roles open on the 0 platforms read; a median of n/a of the 7 steps stated.

Screening depth: how many of the 7 steps in the steps figure a description states.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 4

Screening stated, by platform

Which platforms describe the most screening, and which steps does each state?

Platform	Assessment	AI interview	Interview	Background check	ID check	Credential	Work samples	Median steps	2 or more steps	Roles read	Of its open roles
All described rolesSmall sample	n/a	n/a	n/a	n/a	n/a	n/a	n/a	n/a	n/a	0	n/a

Sample. 0 roles open on 31 Oct 2026 whose job board publishes a full description (none): n/a of the 0 roles open on the 0 platforms read. Only these platforms publish descriptions, so only they are compared here.

Each step column is the share of the platform's described roles that state it.

No row with any described roles is a small sample: the rows differ so much that each reads on its own from its first.

Many descriptions on one platform share a template, so a platform's share often reflects one standard paragraph about its process rather than role-by-role choices.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 5

Screening stated, by kind of work

Which kinds of AI training work are screened the hardest?

No data in this window.

Sample. 0 roles open on 31 Oct 2026 whose job board publishes a full description (none): n/a of the 0 roles open on the 0 platforms read.

A kind's row pools the platforms that publish descriptions. 'From one platform' is the share of its roles listed by the platform with the most of them: near 100%, the row reads that platform's process.

No row with any roles read is a small sample: the rows differ so much that each reads on its own from its first.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 6

What application forms require

Which documents and answers must an applicant give before the form will submit?

Item	Forms asking	Forms requiring it
Resume or CVSmall sample	n/a	n/a
Phone numberSmall sample	n/a	n/a
Location or countrySmall sample	n/a	n/a
LinkedIn profileSmall sample	n/a	n/a
Portfolio, website or GitHubSmall sample	n/a	n/a
Work authorization or visa sponsorshipSmall sample	n/a	n/a
Availability, hours or start dateSmall sample	n/a	n/a
Expected pay or rateSmall sample	n/a	n/a

Sample. 0 application forms of roles open on 31 Oct 2026, read from the applicant-tracking systems of no platform: n/a of the 0 roles open on the 0 platforms read.

Required: the form will not submit without it. Name and email, asked by every form, are not listed.

Work authorization, availability and pay are read from the label of each question the platform adds (the applications report's question themes). The pay theme covers both questions asking an applicant's expected rate and questions asking them to accept the stated rate.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 7

Form burden: required fields per form

How much must an applicant fill in before a form will submit?

Required fields	Forms	Share of forms
4 or fewerSmall sample	0	n/a
5 to 9Small sample	0	n/a
10 to 14Small sample	0	n/a
15 to 19Small sample	0	n/a
20 or moreSmall sample	0	n/a

Sample. 0 application forms of roles open on 31 Oct 2026, read from the applicant-tracking systems of no platform: n/a of the 0 roles open on the 0 platforms read; a median of n/a required fields of n/a in all.

Form burden: the fields a form will not submit without, from name and email to the last required screening question. Some platforms apply in steps (a short form, then an assessment); only the first form is read.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 8

Form burden, by platform

Which platforms ask the most of applicants on the form itself?

Platform	Median required fields	Median fields	Resume required	Phone required	LinkedIn required	Work authorization	Availability	Pay	Forms read	Of its open roles
All forms readSmall sample	n/a	n/a	n/a	n/a	n/a	n/a	n/a	n/a	0	n/a

Sample. 0 application forms of roles open on 31 Oct 2026, read from the applicant-tracking systems of no platform: n/a of the 0 roles open on the 0 platforms read. Only these platforms' forms are read, so only they are compared here.

Work authorization, availability and pay: the share of forms with a required question of that theme.

A platform's medians are stated from 3 forms read (the fewest a middle is stated from); rows with fewer are marked as a small sample and not ranked. Forms of one platform usually share one template, so its medians describe that template.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 9

Screening questions on the form, by platform

What does each platform's form ask applicants about, beyond the resume?

Platform	Work authorization or visa sponsorship	Availability, hours or start date	Expected pay or rate	Degree or field of study	Experience or years in a field	Languages spoken or fluency	Licence or certification	Prior AI training or annotation work	Age or being over 18	Forms read
All forms readSmall sample	n/a	n/a	n/a	n/a	n/a	n/a	n/a	n/a	n/a	0

Sample. 0 application forms of roles open on 31 Oct 2026, read from the applicant-tracking systems of no platform: n/a of the 0 roles open on the 0 platforms read; themes read from the label of each question the platform adds to its form.

Each cell is the share of the platform's forms asking at least one question of the theme. A question can match more than one theme.

Questions on how the applicant heard of the role and voluntary equal-opportunity questions are left out: they do not screen.

No row with any forms read is a small sample: the rows differ so much that each reads on its own from its first.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, October 2026 edition.

Figure 10

Form burden, by kind of work

Do forms for some kinds of AI training work ask more of applicants?

No data in this window.

Sample. 0 application forms of roles open on 31 Oct 2026, read from the applicant-tracking systems of no platform: n/a of the 0 roles open on the 0 platforms read.

A kind's row pools the platforms whose forms are read. 'From one platform' is the share of its forms from the platform with the most of them: near 100%, the row reads that platform's form.

A kind's medians are stated from 3 forms read (the fewest a middle is stated from); rows with fewer are marked as a small sample.

Source. AITraining.jobs Research, How AI Training Platforms Screen Experts, 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.
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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: the full description of each open role where the board publishes one, and the application form of each open role where the platform's applicant-tracking system (Greenhouse, Ashby, Lever, Workable, Teamtailor and others) is read. 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.

Screening step: One of seven checks a description can state: an assessment, test or trial task; an AI-led or recorded interview; an interview with a person or of an unstated kind; a background check; identity verification (the five selection steps); a professional credential or licence; work samples, a portfolio or a publication record (the two kinds of proof of expertise). A step counts when the description states it, as a requirement or as something that may be asked.
Selection passage: The part of a description about applying and being selected: a section headed as the process ('Process', 'Application steps', 'What to expect'), a sentence about the application, onboarding, screening or selection (and the sentence after it), or a sentence about the applicants outside the sections that describe the work or the qualifications. The five selection steps are read only there, with the requirements report's patterns and a few documented additions, so 'conduct psychological assessments' or 'transcribe interviews' in the work is not counted as a check.
Proof of expertise: A professional credential or licence the description names (medical, legal, nursing, financial, board certification or any licence), or work the applicant must show: samples, a portfolio or reel, a verifiable GitHub profile, or a publication record. Read from the whole description, named as a requirement or a preference.
Screening depth: How many of the seven screening steps a description states. Shown as a median and as the share of roles stating two or more.
Form burden: The number of fields an application form will not submit without, from name and email to the last required screening question.
Required: The form will not submit without the field.
Question theme: What a question the platform adds to its form is about (work authorization, availability, pay, degree, experience, languages, a licence, prior AI training work, age), read from its label with the applications report's documented patterns. The pay theme covers both an applicant's expected rate and accepting the stated rate.
Coverage: A platform's board either publishes full descriptions or exposes its application form, and some do neither. Each figure states which platforms and what share of all open roles it reads, and a platform is only ever compared on the source it publishes.
Open role: A role listed by a given day and still in its platform's feed that day.
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.
Window: Live: the roles open at the end of the last 28 complete days, in UTC. Edition: the roles open at the end of one calendar month.

What this data cannot tell you

Stated, not observed: a platform can screen more than its descriptions say, so every share is a floor. Pass rates are not published, so this report cannot say how selective any step is.
Descriptions and forms come from different platforms, and some platforms publish neither: the coverage figure names them. The platforms that publish full descriptions are expert networks, so the description figures lean towards expert work.
Most descriptions and forms on one platform follow one template, so a platform's figure often reflects one standard paragraph or one form, and pooled shares lean on the platform with the most open roles.
Only the first application form is read; assessments and interviews that follow on a platform's own site are visible only when the description states them.
A step phrased in an unusual way can be missed, and a step stated inside a section that describes the work, without a word about applying or selection, is not counted.
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.

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). How AI Training Platforms Screen Experts, October 2026 edition. https://cyberjobs.cc/research/how-ai-training-platforms-screen-experts/2026-10

BibTeX

@misc{aitrainingjobs_how_ai_training_platforms_screen_experts_2026_10,
  author = {{AITraining.jobs}},
  title = {How AI Training Platforms Screen Experts, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://cyberjobs.cc/research/how-ai-training-platforms-screen-experts/2026-10}},
}

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