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Research report ยท October 2026 edition

The Market for Red-Teaming & AI Safety Work

On 31 Oct 2026, 54 roles in Red-Teaming & AI Safety were open on 16 platforms (Alignerr listed 16 of them (29.6%)); their median advertised rate was $80/hr, 100% above the $40/hr of all AI training work; each open role drew 0.45x the apply clicks of the average role.

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

Provisional figures. This month is complete, but late data can still arrive until 3 Nov 2026, when the edition is frozen for good.

Data window
1 Oct 2026 to 31 Oct 2026
31 days, UTC
Computed
1 Nov 2026, 01:18 UTC
Final once frozen
Source
The public job boards of the AI training platforms this site tracks, read every hour. Apply clicks are made on AITraining.jobs; full descriptions come from the platforms whose boards publish them.
Method
Version 5. Definitions
CC BY 4.0, how to cite

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

open roles on 31 Oct 2026
54
median advertised rate (all AI training work: $40/hr)
$80/hr
apply clicks per open role, against the average role
0.45x
of open roles at Alignerr, the largest of 16 platforms
30%

Key findings

  1. 1

    16 platforms listed the 54 open roles in Red-Teaming & AI Safety; Alignerr held 16 of them (29.6%) and the three largest 33 (61.1%) (HHI 1,598, moderately concentrated, against 522 for all AI training work).

    Figure 3
  2. 2

    47 of the 54 open roles in Red-Teaming & AI Safety (87.0%) stated an hourly rate, with a median of $80/hr (typical pay $45 to $125), 100% above the $40/hr of all AI training work.

    Figure 4
  3. 3

    Each open role in Red-Teaming & AI Safety drew 1.55 apply clicks a week on AITraining.jobs, 0.45x the average AI training role: the 4th lowest of 12 kinds of work whose demand reads on its own.

    Figure 6
  4. 4

    20 of the 54 open roles in Red-Teaming & AI Safety (37.0%) accepted applicants from any country, against 18.5% of all AI training roles; of the 20 countries compared, residents of the United States (46), the United Kingdom (42) and Germany (39) could apply to the most, and residents of Palestine to the fewest (25).

    Figure 9
  5. 5

    The words used most in the titles of open roles in Red-Teaming & AI Safety were Red teamer or tester (22), Expert or SME (20) and Specialist (7), of 54 open roles.

    Figure 10
  6. 6

    Of the 38 open roles in Red-Teaming & AI Safety with a full description, 6 (15.8%) mention a PhD or master's degree, 1 (2.6%) a professional credential and 17 (44.7%) an assessment or test; the 11 stating years of experience ask for a median of 3 years.

    Figure 11
  7. 7

    Over the 31 days from 1 Oct 2026 to 31 Oct 2026, platforms listed 19 new roles in Red-Teaming & AI Safety and removed 36, and a removed role had been listed for a median of 80 days (30 across all AI training work).

    Figure 2
  8. 8

    Within Red-Teaming & AI Safety, roles listed during the window drew 4.19 apply clicks per role a week, against 0.04 for roles listed more than 12 weeks before the window.

    Figure 7

Figure 1

Open roles, week by week

Is the number of open roles in Red-Teaming & AI Safety rising or falling?

WeekOpen roles (fixed panel)Index
1 to 4 OctPartial week
27
128.0
5 to 11 OctPartial week
21
100.0
12 to 18 OctPartial week
26
68.2
19 to 25 OctPartial week
29
51.5
26 to 31 OctPartial week
30
53.6

Sample. Average open roles in Red-Teaming & AI Safety over each week's days, on the 18 platforms tracked since 1 Oct 2026 (the fixed panel; 6 of them list this work), 1 Oct 2026 to 31 Oct 2026.

The index is the panel's open roles against the week of 5 Oct 2026 (100), chained week to week, beside the same index for all AI training work on the same platforms.

This site changed how it reads 3 platforms' boards in this span (Alignerr on 14 Oct 2026; OpenTrain AI on 14 Oct 2026; Handshake AI on 14 Oct 2026). From each change to the end of its week the roles that came into view are counted as already listed, not as new listings, and the roles that left view are not counted as removals; changes in open roles are measured like for like across it, on the roles that did not move with it. Each platform's own report says what changed.

SuperAnnotate (SME) (first tracked 10 Oct 2026), Turing (first tracked 10 Oct 2026), Sovrano AI (first tracked 11 Oct 2026), Vetto (first tracked 14 Oct 2026), OneForma (first tracked 14 Oct 2026), Claru (first tracked 14 Oct 2026), Pasiflora AI (first tracked 14 Oct 2026), Weekday (first tracked 18 Oct 2026), Scale AI Human Frontier Collective (first tracked 18 Oct 2026), DataAnnotation (first tracked 22 Oct 2026) and TELUS Digital AI (first tracked 22 Oct 2026) list this work but were added to the dataset later, so they are left out of the panel and counted only in the last column: a platform's arrival never reads as growth.

Every week is marked: the kind's change differs no more than chance from the rest of AI training work's, so its weeks do not read on their own.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 2

Listings added and removed

How fast do roles in Red-Teaming & AI Safety turn over, and is the stock growing on the same platforms?

WorkOpen on 1 Oct 2026Open on 31 Oct 2026, same platformsChangeNew listings
Red-Teaming & AI SafetySmall sample2714
-47.0%
19
All AI training work2,6652,554
-4.2%
1,638

Sample. Roles listed from 1 Oct 2026 to 31 Oct 2026: 93 in Red-Teaming & AI Safety, 7,396 across all AI training work.

Change compares the roles open on the first and the last day of the window on the platforms tracked when it opened, so a platform added during the window does not read as growth.

The kind's change is marked: it differs no more than chance from the rest of AI training work's.

A new listing first appeared in the window on a platform already tracked before that week; a platform's first week (its back catalogue) is not counted.

Median days listed runs from a removed role's listing date to its last sighting, for removed roles with a known listing date (at least 3; 33 here).

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 3

Who lists it

Which platforms list roles in Red-Teaming & AI Safety, and what does each advertise?

PlatformOpen rolesShare of open rolesMedian per hour
Alignerr16
29.6%
$60
SuperAnnotate (SME)12
22.2%
n/a
Mercor5
9.3%
n/a
Handshake AI3
5.6%
$95
micro13
5.6%
$85
DataAnnotation2
3.7%
n/a
OpenTrain AI2
3.7%
n/a
Turing2
3.7%
n/a
Vetto2
3.7%
n/a
AfterQuery1
1.9%
n/a
Claru1
1.9%
n/a
Pasiflora AI1
1.9%
n/a
Scale AI Human Frontier Collective1
1.9%
n/a
Sovrano AI1
1.9%
n/a
TELUS Digital AI1
1.9%
n/a
Weekday1
1.9%
n/a

Sample. 54 roles in Red-Teaming & AI Safety open at the end of 31 Oct 2026, by the platform that lists them: HHI 1,598 (moderately concentrated), against 522 for all AI training work.

HHI: the sum of every platform's squared percentage share of the open roles, 0 to 10,000; under 1,500 is unconcentrated, 1,500 to 2,500 moderately and above 2,500 highly concentrated (US merger-guideline thresholds).

Shares are of listings, not of people hired or money paid: a platform posting one role per language or country weighs more here than its hiring may.

A median needs at least 3 roles stating an hourly rate.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 4

What it pays

What do roles in Red-Teaming & AI Safety advertise per hour, against AI training work as a whole?

WorkMedian per hourTypical pay fromTypical pay toStating an hourly rate
Red-Teaming & AI Safety
$80
$45$12587.0%
All AI training work
$40
$30$12581.4%

Sample. Roles open on 31 Oct 2026: 54 in Red-Teaming & AI Safety, 47 of them stating an hourly rate; 4,381 across all AI training work.

Pay is the hourly figure a posting advertises (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.

Roles paid per task or per project, or that state no figure, do not state an hourly rate.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 5

How its rates are distributed

What share of roles in Red-Teaming & AI Safety pay $50 an hour or more?

Advertised rateOpen rolesShare of priced rolesAll AI training work
Under $15/hr0
0.0%
6.9%
$15 to $25/hr0
0.0%
10.6%
$25 to $35/hr1
2.1%
11.9%
$35 to $50/hr11
23.4%
26.0%
$50 to $75/hr11
23.4%
14.7%
$75 to $100/hr16
34.0%
15.3%
$100 to $150/hr7
14.9%
9.4%
$150/hr or more1
2.1%
5.1%

Sample. 47 roles in Red-Teaming & AI Safety open on 31 Oct 2026 that state an hourly rate, against 3,565 across all AI training work.

Each role counts once, at the middle of its advertised range. The bands are those of the pay-transparency report.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 6

Applicant demand per open role

Do roles in Red-Teaming & AI Safety draw more or fewer applicants per opening than the average AI training role?

RolesClicks per role a weekIndex
Red-Teaming & AI Safety
1.55
0.45x
All AI training work
3.41
1.00x
Its roles stating an hourly rate
1.65
0.48x
Its roles stating no hourly rate
0.80
0.23x
Its roles open worldwide
0.14
0.04x
Its roles limited by country
2.31
0.68x

Sample. Apply clicks on a specific role on AITraining.jobs, from 1 Oct 2026 to 31 Oct 2026: 282 on roles in Red-Teaming & AI Safety, against the days those roles were open.

Clicks per role a week = apply clicks / (open role-days / 7). Index 1.00 is the rate of every role on the site.

Red-Teaming & AI Safety against every kind of work: Rows with fewer than 3.6 open role-days (0.5 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the kinds of work weighs more than a row's own clicks (the weight fitted on their own clicks).

Its roles by stated pay, against each other: Rows with fewer than 35.4 open role-days (5.1 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the two sides weighs more than a row's own clicks (the weight fitted on their own clicks). Its roles by reach, against each other: Rows with fewer than 3.4 open role-days (0.5 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the two sides weighs more than a row's own clicks (the weight fitted on their own clicks). All AI training work is one set, read from its first open role-day.

Apply clicks measure interest among visitors to AITraining.jobs, who see roles open in their country and recent, priced roles first. Clicks are never split by platform.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 7

Applicant demand by listing age

Do newer roles in Red-Teaming & AI Safety draw more applicants than older ones?

Listing ageClicks per role a weekIndex (this work = 1)
Listed during the window
4.19
2.71x
Listed up to 4 weeks before it
0.25
0.16x
Listed 4 to 12 weeks before it
8.08
5.22x
Listed more than 12 weeks before it
0.04
0.02x
Listing date unknown
0.23
0.15x

Sample. Apply clicks on roles in Red-Teaming & AI Safety, from 1 Oct 2026 to 31 Oct 2026, by when each role was listed relative to the window's first day (1 Oct 2026).

Listing date: the date the job board gives for the posting, or else the first day the role appeared in the feed. A role that arrived with a platform's back catalogue and gives no date has none.

The index divides each row's rate by the rate of all roles in this kind of work, so it reads within the kind.

Rows with fewer than 1.8 open role-days (0.3 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the listing ages weighs more than a row's own clicks (the weight fitted on their own clicks).

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 8

Who may apply: location rules

Can people apply to roles in Red-Teaming & AI Safety from anywhere?

Location ruleOpen rolesShare of its open rolesAll AI training work
Open worldwide20
37.0%
18.5%
Worldwide except listed countries13
24.1%
18.1%
Only listed countries21
38.9%
63.0%
No rule stated0
0.0%
0.4%

Sample. 54 roles in Red-Teaming & AI Safety open at the end of 31 Oct 2026, against 4,381 across all AI training work.

The rule is read from each posting's location text, then, where that names no country, from what the posting's own description states, and where both are silent from what the platform states about where it hires.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 9

Who may apply: roles open to each country

How many roles in Red-Teaming & AI Safety can a resident of each country apply to?

CountryOpen rolesShare of its open roles
Any country (worldwide roles only)
20
37.0%
United States
46
85.2%
United Kingdom
42
77.8%
Germany
39
72.2%
India
34
63.0%
Indonesia
33
61.1%
Philippines
33
61.1%
Argentina
32
59.3%
Bangladesh
32
59.3%
Chile
32
59.3%
Colombia
32
59.3%
Egypt
32
59.3%
Ghana
32
59.3%
Japan
32
59.3%
South Korea
32
59.3%
Nigeria
32
59.3%
Saudi Arabia
32
59.3%
Brazil
30
55.6%
Pakistan
28
51.9%
Cambodia
27
50.0%
Palestine
25
46.3%

Sample. 54 roles in Red-Teaming & AI Safety open at the end of 31 Oct 2026, for residents of a fixed set of 20 countries.

A country's count is the roles open worldwide (including roles that state no rule, as on the job board), plus roles whose list names it, plus roles whose exclusion list does not.

The 20 countries are the same in every report of this series: those named most often by the location rules of open AI training roles on 9 Oct 2026, either as the only countries accepted or as excluded.

Median pay is over the roles open to that country that state an hourly rate (at least 3).

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 10

What the roles are called

What are roles in Red-Teaming & AI Safety called: annotator, evaluator, expert or trainer?

Title wordOpen rolesShare of its open roles
Red teamer or tester
22
40.7%
Expert or SME
20
37.0%
Specialist
7
13.0%
Analyst or researcher
6
11.1%
Engineer or developer
3
5.6%
Evaluator or reviewer
3
5.6%
Annotator or labeler
1
1.9%

Sample. 51 of the 54 roles in Red-Teaming & AI Safety open on 31 Oct 2026 name one of these words in their title (94.4%); 7 title words are named.

A title can use several of these words ('Expert AI Trainer') and counts for each. The vocabularies are those of the job-titles, languages and expert-fields reports.

Median pay needs at least 3 roles stating an hourly rate.

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

Figure 11

What the descriptions ask for

Do roles in Red-Teaming & AI Safety ask for degrees, credentials, experience or tests?

RequirementRolesShare of described roles
Mentions a PhD5
13.2%
Mentions a PhD or master's6
15.8%
Mentions any degree15
39.5%
Mentions a professional credential1
2.6%
States years of experience11
28.9%
Asks for 5 years or more0
0.0%
States weekly hours5
13.2%
Mentions an assessment or test17
44.7%
Mentions an AI-led or video interview0
0.0%
Mentions a background check0
0.0%

Sample. 38 roles in Red-Teaming & AI Safety open on 31 Oct 2026 whose job board publishes a full description (AfterQuery, Claru, DataAnnotation, Handshake AI, Mercor, micro1, OpenTrain AI, Pasiflora AI, Scale AI Human Frontier Collective, Sovrano AI, SuperAnnotate (SME), TELUS Digital AI, Turing, Vetto and Weekday), 70.4% of its open roles; 4,000 described roles across all AI training work.

A mention can be a requirement or a preference ('a PhD is a plus'): the figure counts both. The patterns are those of the requirements report.

Only some platforms publish full descriptions, so this figure describes their roles, not every platform's.

A kind of work's figure is shown when its described roles outweigh the average of the kinds (5.8 described roles: the weight of every kind's shares around the shares of all described roles, fitted on their own counts).

Source. AITraining.jobs Research, The Market for Red-Teaming & AI Safety Work, October 2026 edition.

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Method and definitions

The public job boards of the AI training platforms this site tracks, read every hour. Apply clicks are made on AITraining.jobs; full descriptions come from the platforms whose boards publish them. 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.

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; this report counts the roles classified as Red-Teaming & AI Safety.
Fixed panel
The platforms already tracked when the weekly series opens. The index follows their open roles, so a platform added later (such as OpenTrain AI and Welo Data in September 2026) never reads as growth.
Index
The panel's average open roles in a week, divided by the same in the base week, times 100; shown beside the same index for all AI training work on the same platforms.
Open role
A role listed by a given day and still in its platform's feed that day.
New listing
A role that first appeared during the window on a platform already tracked before that week. A platform's first week in this dataset is its back catalogue and is not counted as new. When this site changes how it reads a platform's board (a cap lifted, a page kind or department read too, a relevance rule changed), the roles that came into view or left it from that change to the end of its week are this site's reading, not the platform's hiring: they are not new listings or removals, and changes in open roles are measured like for like across it. Each platform's report says what changed.
Removed listing
A role that left its platform's feed during the window.
Days listed
From a removed role's listing date to the last day it was seen in its feed. A median needs at least 3 removed roles.
HHI
Herfindahl-Hirschman Index: the sum of every platform's squared percentage share of open roles, 0 to 10,000. Under 1,500 unconcentrated, 1,500 to 2,500 moderately, above 2,500 highly concentrated.
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.
Clicks per open role a week
Apply clicks on AITraining.jobs on a specific role, divided by the days the roles were open, times 7.
Demand index
Clicks per open role a week divided by the same rate across every role on the site. Above 1, the roles draw more applicants than the average role.
Listing age
When a role was listed relative to the window's first day: during the window, up to 4 weeks before it, 4 to 12 weeks before or longer. The listing date is the job board's posting date, or else the first day the role appeared in the feed.
Location rule
Read from each posting's location text and, where that names no country, from what the posting's own description states: open worldwide, worldwide except listed countries, only listed countries, or no rule stated.
Open to a country
A role is open to residents of a country if it is open worldwide, its list names the country, or its exclusion list does not. The 20 countries compared are the same in every report of the series.
Window
Live: the last 28 complete days, in UTC, and the last twelve complete ISO weeks (from the week of 3 Aug 2026 at the earliest) for the weekly series. Edition: one calendar month, in UTC, and its weeks.

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.
  • Apply clicks measure interest among the people who use AITraining.jobs, and what is shown first gets clicked more. Clicks are never published by platform.
  • Full descriptions are published by a few platforms only, so the requirements figure describes their roles and appears only when this kind's described roles read on their own against the other kinds' (the weight of every kind's shares around the shares of all described roles, fitted on their own counts).
  • A kind of work with few open roles gives figures that move with a handful of postings: rows on too little data are marked as a small sample.

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.

Cite and reuse

Free to quote, chart and republish under CC 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). The Market for Red-Teaming & AI Safety Work, October 2026 edition. https://aitraining.jobs/research/red-teaming-ai-safety-market/2026-10

BibTeX

@misc{aitrainingjobs_red_teaming_ai_safety_market_2026_10,
  author = {{AITraining.jobs}},
  title = {The Market for Red-Teaming & AI Safety Work, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://aitraining.jobs/research/red-teaming-ai-safety-market/2026-10}},
}
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