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Research report ยท October 2026 edition

OpenTrain AI Hiring Data

On 31 Oct 2026, OpenTrain AI listed 40 open AI training roles (0.9% of the market, the 28th largest of 62 platforms), 22.5% of them in Transcription, Audio & Speech; all stated an hourly rate, at a median of $30/hr, and 70.0% accepted applicants worldwide except listed countries.

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, 01:17 UTC
Final once frozen
Source
The public job boards of the AI training platforms this site tracks, read every hour. OpenTrain AI's figures come from its own public listings only; full descriptions and application forms are read where its job board publishes 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.

Key findings

  1. 1

    OpenTrain AI listed 40 open roles on 31 Oct 2026, 0.9% of the 4,381 open across the 62 platforms AITraining.jobs reads, the 28th most.

    Figure 1
  2. 2

    As this site read it, OpenTrain AI went from 699 open roles on 4 Oct 2026 to 40 on 31 Oct 2026, but that count changed with our reading of its board as well as with its hiring: roles came into and left view when this site changed how it reads the board on 14 Oct 2026. Measured on the roles that did not move with it, like for like its open roles went down 7.5%.

    Figure 2
  3. 3

    22.5% of its open roles are in Transcription, Audio & Speech, where OpenTrain AI holds 1.4% of all open roles, the joint 14th largest share of 31 platforms; it lists 9 of the 12 kinds of work with open roles.

    Figure 3
  4. 4

    On 31 Oct 2026, all 40 of its open roles stated an hourly rate. Their 40 distinct advertised rates have a median of $30/hr and typical pay of $15 to $60/hr, against a median of $40/hr across other platforms' rates.

    Figure 4
  5. 5

    Compared within the same kinds of work (5 with enough rates on both sides), the advertised median at OpenTrain AI runs 45.8% below other platforms' and is lower in all 5; the widest gap is in Data Annotation & Labeling ($10/hr against $30/hr).

    Figure 4
  6. 6

    None of its 40 open roles are open to applicants in any country (18.7% on other platforms); 30.0% are limited to listed countries, naming France, Italy and the United States and 18 more; 70.0% exclude the same 79 countries, among them Afghanistan, Andorra and Barbados.

    Figure 6
  7. 7

    From 1 Oct 2026 to 31 Oct 2026, OpenTrain AI posted 208 new listings and removed 335 (listed a median of 29.4 days before removal, against 32.9 days on other platforms); its open roles went from 804 to 40 as read, and went down 19.6% like for like, across the change in how this site reads its board on 14 Oct 2026.

    Figure 9
  8. 8

    Of the 40 roles OpenTrain AI lists with a full description, 12.5% mention a PhD or master's degree, 2.5% a professional credential and 7.5% an assessment or test (other platforms with descriptions: 25.3%, 16.7% and 20.1%).

    Figure 14

Figure 1

OpenTrain AI against the other platforms

How does OpenTrain AI compare with the rest of the market on size, pay, reach and turnover?

MeasureOpenTrain AIOther platformsIts rank (1 = highest)
Open roles on 31 Oct 2026404,34128th of 62
Share of all open roles0.9%99.1%28th of 62
New listings in the window2081,4304th of 62
Kinds of work listed912joint 9th of 62
Open roles stating an hourly rate100.0%81.2%joint 1st of 62
Median advertised pay$30/hr$40/hrjoint 23rd of 37
Open roles accepting any country0.0%18.7%joint 24th of 62
Median days listed, removed roles29.4 days32.9 days18th of 26

Sample. 40 roles OpenTrain AI listed open at the end of 31 Oct 2026, beside the 4,341 open on the other 61 platforms AITraining.jobs reads; listings from 1 Oct 2026 to 31 Oct 2026.

Other platforms: every other platform read over the same window, pooled (counts are summed, medians are taken over all their distinct rates together).

Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

Rank among the 62 platforms with open roles. A share is ranked where the platform's open roles outweigh the average of the platforms it leans on, the weight fitted on every platform's own count (here 0.8 open roles for stating a rate, 0.4 open roles for accepting any country); a pay median needs 3 distinct advertised rates and days listed 3 removed roles with a known listing date. A platform below one is not ranked on it. Days listed rank longest first.

Listings only: what the platform's public job board shows.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 2

Open roles at OpenTrain AI, week by week

Is OpenTrain AI listing more AI training roles or fewer?

WeekOpen roles, like for like (first week = 100)Open at the end of the week, as readNew listings
1 to 4 OctPartial week
100.0
69940
5 to 11 Oct
99.7
69792
12 to 18 Oct (our reading changed)Partial week
97.1
42n/a
19 to 25 Oct
92.5
4029
26 to 31 OctPartial week
92.5
407

Sample. Listings by OpenTrain AI, by ISO week (Monday to Sunday, UTC), 1 Oct 2026 to 31 Oct 2026; 5 weeks tracked.

Open roles are counted at the end of each week (Sunday, UTC), or at the end of the window for a week it cuts. New listings leave out roles that came with the platform's back catalogue.

Like for like: open roles against the first week with open roles (100), measured across any change in what AITraining.jobs reads of the board on the roles that neither came into view nor left it with the change, so our reading never reads as hiring.

On 14 Oct 2026 our reading of OpenTrain AI changed: this site left out the roles OpenTrain re-lists from platforms this site reads from their own boards (655 of its 698 open roles), so each is counted once, on its own platform. From then to the end of that week (18 Oct 2026) 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, and its open roles are compared like for like across the change.

A week the window cuts is labelled with the days it covers and marked as partial.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 3

What OpenTrain AI hires for

Which kinds of AI training work does OpenTrain AI list, and how much of each market does it hold?

Kind of workOpen rolesShare of its rolesIts share of the kind's open roles
Transcription, Audio & Speech
9
22.5%1.4%
Law, Medicine & Finance
7
17.5%0.5%
Math & STEM
7
17.5%2.8%
Data Annotation & Labeling
6
15.0%2.5%
Agentic Tasks & RL EnvironmentsSmall sample
4
10.0%3.2%
Coding & Software Evaluation
2
5.0%0.7%
Red-Teaming & AI SafetySmall sample
2
5.0%3.7%
AI Evaluation & Rating (RLHF)
2
5.0%1.0%
Multilingual & Localization
1
2.5%0.1%

Sample. 40 roles OpenTrain AI listed open at the end of 31 Oct 2026; market shares are of the 4,381 roles open on all 62 platforms that day.

Kinds of work are this site's twelve categories of AI training work, each role classified from its title and description.

Its rank in the kind is among the platforms with open roles in it. A median needs at least 3 distinct advertised rates, as on the job board.

Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

Rows with fewer than 178 open roles in the kind are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own open roles in the kind (the weight fitted on the rows' own counts).

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 4

What OpenTrain AI advertises it pays

How often does OpenTrain AI state its pay, and how does it compare with other platforms for the same work?

RolesStating an hourly rateIts median per hourOther platforms' medianIts median against theirs
All its open roles100.0%
$30
$40-31.2%
Compared within the same kinds of work (5)n/a
n/a
n/a-45.8%
Transcription, Audio & Speech100.0%
$15
$30-50.0%
Law, Medicine & Finance100.0%
$30
$75-56.7%
Math & STEM100.0%
$40
$40-6.2%
Data Annotation & Labeling100.0%
$10
$30-67.3%
Agentic Tasks & RL Environments100.0%
$30
$65-53.8%
Coding & Software EvaluationSmall sample100.0%
n/a
$60n/a
Red-Teaming & AI SafetySmall sample100.0%
n/a
$80n/a
AI Evaluation & Rating (RLHF)Small sample100.0%
n/a
$35n/a
Multilingual & LocalizationSmall sample100.0%
n/a
$35n/a

Sample. 40 of the 40 roles OpenTrain AI listed open on 31 Oct 2026 state an hourly rate, 40 distinct rates and 0 advertised maximums; other platforms: 3,525 of 4,341.

Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

A median needs at least 3 distinct advertised rates, as on the job board. A comparison within a kind of work needs 3 distinct rates on each side. The row compared within the same kinds of work averages the kinds where both sides have enough, weighted by the platform's distinct rates in each, so a platform listing better-paid work is not read as paying more for the same work.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 5

What OpenTrain AI advertises it pays, week by week

Is OpenTrain AI advertising higher or lower pay than it did?

WeekMedian per hourTypical pay
1 to 4 OctPartial week
$50
$25 to $170
5 to 11 Oct
$50
$25 to $170
12 to 18 Oct
$30
$15 to $60
19 to 25 Oct
$30
$15 to $60
26 to 31 OctPartial week
$30
$15 to $60

Sample. Roles OpenTrain AI listed open at the end of each ISO week (Monday to Sunday, UTC) that state an hourly rate, 1 Oct 2026 to 31 Oct 2026.

Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list. Each week is measured over the roles open at its end.

A week needs at least 3 distinct advertised rates for a median.

A change can come from roles listed or removed at other rates as well as from a rate changed on a role: it describes what the board advertised, not what any one worker was paid.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 6

Who may apply to roles at OpenTrain AI

Are the roles OpenTrain AI lists open to applicants anywhere, or limited to some countries?

Location ruleIts open rolesShare of its rolesShare on other platforms
Open worldwide0
0.0%
18.7%
Worldwide except listed countries28
70.0%
17.6%
Only listed countries12
30.0%
63.3%
No rule stated0
0.0%
0.4%

Sample. 40 roles OpenTrain AI listed open on 31 Oct 2026, against the 4,341 open on other platforms.

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. A rule says where applications are accepted; tax, payment and work-permit rules can still apply.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 7

Countries OpenTrain AI names in its limited roles

When OpenTrain AI limits a role to some countries, which countries does it name?

CountryLimited roles naming itShare of its limited roles
France
3
25.0%
Italy
3
25.0%
United States
3
25.0%
Australia
2
16.7%
Canada
2
16.7%
Malaysia
2
16.7%
New Zealand
2
16.7%
Portugal
2
16.7%
United Kingdom
2
16.7%
ArgentinaSmall sample
1
8.3%
Costa RicaSmall sample
1
8.3%
GuatemalaSmall sample
1
8.3%

Sample. 12 of the 40 roles OpenTrain AI listed open on 31 Oct 2026 accept applicants only from listed countries; 7 of them name a single country. The 12 countries named most often, of 21.

A role naming several countries counts for each. Open only there: roles whose list names this country alone.

A row is marked as a small sample where the platform's limited roles do not outweigh the average of the platforms for that country (the weight fitted on every platform's own count).

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 8

Countries OpenTrain AI excludes

Which countries does OpenTrain AI leave out of roles otherwise open worldwide?

CountryRoles excluding itShare of such roles
Afghanistan
28
100.0%
Andorra
28
100.0%
Barbados
28
100.0%
Belarus
28
100.0%
Belize
28
100.0%
Brazil
28
100.0%
Burkina Faso
28
100.0%
Burundi
28
100.0%
Cameroon
28
100.0%
Cape Verde
28
100.0%
Central African Republic
28
100.0%
Chad
28
100.0%
China
28
100.0%
Comoros
28
100.0%
Congo (Republic)
28
100.0%

Sample. 28 of the 40 roles OpenTrain AI listed open on 31 Oct 2026 are open worldwide except listed countries; 79 countries are excluded by at least one, the 15 excluded most often shown (every one of these roles excludes the same list).

Exclusions usually follow payment and sanctions rules: where a platform cannot pay or contract, not where it has no work.

A row is marked as a small sample where the platform's excluding roles do not outweigh the average of the platforms for that country (the weight fitted on every platform's own count).

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 9

Listings posted and removed by OpenTrain AI

How many roles did OpenTrain AI post and take down?

MeasureRoles
Open at the start of 1 Oct 2026
804
New listings
208
Removed listings
335
Open at the end of 31 Oct 2026
40

Sample. Listings by OpenTrain AI from 1 Oct 2026 to 31 Oct 2026.

New listings: roles first seen in the window, outside the platform's first week in this dataset and outside the week of a change in how this site reads its board. Removed: roles that left the feed during the window, other than with such a change. A role can be both.

On 14 Oct 2026 our reading of OpenTrain AI changed: this site left out the roles OpenTrain re-lists from platforms this site reads from their own boards (655 of its 698 open roles), so each is counted once, on its own platform. From then to the end of that week (18 Oct 2026) 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, and its open roles are compared like for like across the change.

The other platforms' count at the start leaves out platforms first tracked during the window.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 10

How long roles at OpenTrain AI stayed up

How long had the roles OpenTrain AI removed been listed?

Days listedRemoved rolesShare
Under 7 days23
6.9%
7 to 13 days46
13.7%
14 to 29 days129
38.5%
30 to 59 days103
30.7%
60 days or more34
10.1%

Sample. 335 roles OpenTrain AI removed from 1 Oct 2026 to 31 Oct 2026 with a known listing date; median 29.4 days (other platforms: 32.9 days over 1,563 roles).

Days listed: from the listing date the job board states (or the first day the role appeared in the feed) to the last day it was seen. Roles that arrived with the back catalogue and state no date are left out.

A median needs at least 3 removed roles. A removed role may have been filled, paused or closed: platforms do not say which.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 11

What OpenTrain AI calls the work

Which words does OpenTrain AI use in its job titles: trainer, tutor, expert, rater, annotator?

Title wordIts open rolesShare of its rolesShare on other platforms
Annotator or labeler
13
32.5%6.5%
Expert or SME
10
25.0%24.8%
Specialist
7
17.5%18.7%
Evaluator or reviewer
6
15.0%8.2%
Engineer or developer
5
12.5%8.0%
Quality assurance
4
10.0%4.4%
Red teamer or testerSmall sample
2
5.0%0.7%
Trainer
2
5.0%18.8%
Writer or editor
2
5.0%1.5%
None of these words
4
10.0%16.6%

Sample. 40 roles OpenTrain AI listed open on 31 Oct 2026, by the words in their titles (the same vocabulary as the job titles report).

A title can use several words ('Expert AI Trainer') and counts for each, so shares add to more than 100%. Whole words, case-insensitive.

A median needs at least 3 distinct advertised rates, as on the job board. Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

A word is marked as a small sample where OpenTrain AI's open roles do not outweigh the average of the platforms for that word (the weight fitted on every platform's own count).

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 12

Languages OpenTrain AI hires for

Which languages does OpenTrain AI name in its job titles?

LanguageIts open rolesShare of its rolesIts share of all roles naming the language
EnglishSmall sample
4
10.0%2.1%
Chinese (Mandarin)Small sample
2
5.0%2.6%
FrenchSmall sample
2
5.0%2.2%
JapaneseSmall sample
1
2.5%1.8%
KoreanSmall sample
1
2.5%1.8%

Sample. 8 of the 40 roles OpenTrain AI listed open on 31 Oct 2026 name a language in the title (5 languages).

Read from titles with the vocabulary of the languages report (whole words); a title naming two counts for both, and a role that needs a language without naming it is not counted.

A median needs at least 3 distinct advertised rates, as on the job board. Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

Every row is marked as a small sample: the rows differ no more than chance makes them, so none reads on its own and none is ranked.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 13

Expert fields OpenTrain AI hires for

Which professions and disciplines does OpenTrain AI name in its job titles?

FieldIts open rolesShare of its rolesIts share of all roles naming the field
Software and ITSmall sample
6
15.0%1.5%
Engineering (non-software)Small sample
5
12.5%2.3%
Data science and machine learningSmall sample
3
7.5%4.5%
Mathematics and statisticsSmall sample
3
7.5%2.7%
Finance and accountingSmall sample
2
5.0%0.8%
Biology and life sciencesSmall sample
1
2.5%1.1%
Nuclear, CBRN and defenseSmall sample
1
2.5%2.1%
ChemistrySmall sample
1
2.5%1.1%
TeachingSmall sample
1
2.5%2.7%
LawSmall sample
1
2.5%0.6%
Medicine and nursingSmall sample
1
2.5%0.4%
Physics and astronomySmall sample
1
2.5%1.3%

Sample. 23 of the 40 roles OpenTrain AI listed open on 31 Oct 2026 name a field in the title (13 fields, the 12 named most often shown).

Read from titles with the vocabulary of the expert fields report (whole words); a title naming two counts for both, and a role that needs a field without naming it is not counted.

A median needs at least 3 distinct advertised rates, as on the job board. Pay is measured as on the job board: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20), as on every list.

Every row is marked as a small sample: the rows differ no more than chance makes them, so none reads on its own and none is ranked.

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, October 2026 edition.

Figure 14

What roles at OpenTrain AI ask for

Do the roles OpenTrain AI lists ask for degrees, credentials, experience, set hours or tests?

The descriptionIts rolesShare of its roles readOther platforms with descriptions
Mentions a PhD or doctorate4
10.0%
17.4%
Mentions a PhD or master's degree5
12.5%
25.3%
Mentions a degree9
22.5%
38.8%
Mentions a professional credential1
2.5%
16.7%
States years of experience5
12.5%
26.1%
States weekly hours20
50.0%
24.3%
Mentions an assessment, test or trial task3
7.5%
20.1%
Mentions an interview of any kind0
0.0%
10.0%
Mentions an AI-led or recorded interview0
0.0%
5.0%
Mentions a background or identity check0
0.0%
1.4%
Mentions contractor or freelance terms32
80.0%
52.1%

Sample. The full descriptions of 40 of the 40 roles OpenTrain AI listed open on 31 Oct 2026, against 3,960 roles of the other platforms whose boards publish them (AfterQuery, Aligned Labs, Anthropic, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Cohere, DataAnnotation, DATAmundi, Edison Scientific, Elsevier Health, EvolutionIQ, Fleet AI, Handshake AI, Headway, iMerit, Innodata, Invisible, Inworld AI, JazzX AI, Kastle, Lifted (Upwork), Limbic, Mercor, micro1, Mindrift, Mistral AI, OneForma, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, PointClickCare, Prolific, RealTrainAI, RemoExperts, Remotasks, Rise Data Labs, RWS TrainAI Community, Sama, Scale AI Human Frontier Collective, Shaip (Collaborate by Shaip), Sigma AI, Snorkel AI Expert Community, Sovrano AI, SuperAnnotate (SME), Surge AI, TELUS Digital AI, Terac, TransPerfect DataForce, Trellis, Turing, Vals AI, Vetto, Volga Partners, Weekday, Welo Data and xAI (SpaceXAI)). Median years asked: 5. Median weekly hours stated: 20.

Read with the documented patterns of the requirements report (whole words, case-insensitive). A mention can be a requirement or a preference ('a PhD is a plus'): both count.

Medians of years and hours need at least 3 roles stating them (the one minimum of every median); for hours the lower figure of a range counts.

Rows with fewer than 1.7 described roles are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own described roles (the weight fitted on the rows' own counts).

Source. AITraining.jobs Research, OpenTrain AI Hiring Data, 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. OpenTrain AI's figures come from its own public listings only; full descriptions and application forms are read where its job board publishes 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.

Other platforms
Every platform this site reads other than OpenTrain AI, over the same window and pooled: counts are summed and medians are taken over all their rates together. OpenTrain AI is compared with the rest of the market, not with a market that includes it.
Rank
Its place among the platforms with open roles on the last day of the window, highest first (longest first for days listed). A share is ranked where the platform's open roles read on their own among the platforms (they reach the weight of the platforms' average share, fitted on their own counts), a pay median from 3 distinct advertised rates and days listed from 3 removed roles, so a platform below one is not ranked on that measure.
Open role
A role listed by a given day and still in its platform's feed that day. Week by week, open roles are counted at the end of each week (Sunday, UTC).
Back catalogue
The roles already listed in the week a platform was first tracked. That week is marked in the weekly series and its roles are not counted as new listings; weeks before it are left out.
New listing
A role that first appeared during the window on a platform already tracked before that week, other than with a change in how this site reads its board (below).
Removed listing
A role that left its platform's feed during the window, other than with a change in how this site reads its board (below). When most removals or new listings fall on one day, the figure says so: one large change to a board moves the window's flow.
Change in our reading
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. For OpenTrain AI: on 13 Sep 2026 this site re-judged every posting with the second version of its relevance check (robot and embodied-AI data work added), which left out some postings it had kept and kept some it had left out; on 22 Sep 2026 this site began reading job pages that carry no JobPosting block, from the details the page shows, after nine days in which five such pages had stopped every read of its board; on 14 Oct 2026 this site left out the roles OpenTrain re-lists from platforms this site reads from their own boards (655 of its 698 open roles), so each is counted once, on its own platform.
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 with a known listing date.
Advertised pay
Measured exactly as the job board measures any list of roles, so a median here is the median OpenTrain AI's pay page states for the same roles: one sample per distinct advertised rate (the middle of a stated range; a role posted again at the same rate counts once), and an advertised maximum ("up to $X/hr") is a ceiling, not a rate, so it is counted and left out. Typical pay is the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling; it and the median are rounded to $5 ($1 under $20) and need at least 3 distinct rates.
Compared within the same kinds of work
For each kind of work where both the platform and the other platforms state at least 3 distinct hourly rates, its median over theirs, minus one; averaged across those kinds, weighted by the platform's distinct rates, so a platform listing better-paid work is not read as paying more for the same work. It needs two such kinds.
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.
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. Every kind links to its own page.
Title word, language, field
Read from titles as whole words with the vocabularies of the job titles, languages and expert fields reports; a title can count for several.
Mention
A description mentions a degree, credential, step or term when it contains one of the patterns published in the requirements report. A mention may be a requirement or a preference.
Application form
The fields an applicant fills in on the platform's own application page, read from its applicant-tracking system. Required: the form will not submit without the field.
Window
Live: the last 28 complete days, in UTC, with the weekly series over the last twelve complete ISO weeks from the week of 3 Aug 2026 at the earliest. Edition: one calendar month, in UTC, its weeks cut at the month's edges.

What this data cannot tell you

  • Platforms that recruit without a public job board are not counted, and a platform may staff projects it never lists: its listings are what it advertises, not everything it hires for.
  • A listing is not a hire. Some platforms keep evergreen roles open for months, and some post one listing per language or country.
  • Listings only: how many people apply to a platform is never published here.
  • Pay is what postings advertise, not what workers are paid after bonuses, tiers or rejected tasks.
  • Full descriptions and application forms are published by some job boards only, so those figures appear only for the platforms whose boards publish them, and describe the roles open on the day they were read.
  • A removed listing may have been filled, paused or closed: platforms do not say which.

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). OpenTrain AI Hiring Data, October 2026 edition. https://aitraining.jobs/research/opentrain-ai-hiring-data/2026-10

BibTeX

@misc{aitrainingjobs_opentrain_ai_hiring_data_2026_10,
  author = {{AITraining.jobs}},
  title = {OpenTrain AI Hiring Data, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://aitraining.jobs/research/opentrain-ai-hiring-data/2026-10}},
}
Data: every figure as CSV (one line per value) and JSON, sent to your work email.Pay and open-roles data

More research

The same figures for every other platform:

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