Key findings

1
19 platforms listed the 124 open roles in Agentic Tasks & RL Environments; Mercor held 28 of them (22.6%) and the three largest 67 (54.0%) (HHI 1,270, unconcentrated, against 522 for all AI training work).
Figure 3
2
103 of the 124 open roles in Agentic Tasks & RL Environments (83.1%) stated an hourly rate, with a median of $65/hr (typical pay $45 to $120), 63% above the $40/hr of all AI training work.
Figure 4
3
Each open role in Agentic Tasks & RL Environments drew 1.22 apply clicks a week on AITraining.jobs, 0.36x the average AI training role: the 3rd lowest of 12 kinds of work whose demand reads on its own.
Figure 6
4
9 of the 124 open roles in Agentic Tasks & RL Environments (7.3%) accepted applicants from any country, against 18.5% of all AI training roles; of the 20 countries compared, residents of the United States (84), India (80) and the United Kingdom (74) could apply to the most, and residents of Palestine to the fewest (25).
Figure 9
5
The words used most in the titles of open roles in Agentic Tasks & RL Environments were Engineer or developer (42), Trainer (29) and Expert or SME (20), of 124 open roles.
Figure 10
6
Of the 120 open roles in Agentic Tasks & RL Environments with a full description, 47 (39.2%) mention a PhD or master's degree, 18 (15.0%) a professional credential and 9 (7.5%) an assessment or test; the 22 stating years of experience ask for a median of 3 years.
Figure 11
7
Over the 31 days from 1 Oct 2026 to 31 Oct 2026, open roles in Agentic Tasks & RL Environments on the platforms tracked at its start went up 115.5% (67 to 144, like for like across the changes in how this site reads some of their boards): platforms listed 89 new roles and removed 39, and a removed role had been listed for a median of 30 days (30 across all AI training work).
Figure 2
8
Within Agentic Tasks & RL Environments, roles listed during the window drew 4.08 apply clicks per role a week, against 0.17 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 Agentic Tasks & RL Environments rising or falling?

Week	Open roles (fixed panel)	Index	All AI training work (index)	All tracked platforms
1 to 4 OctPartial week	58	114.9	103.2	58
5 to 11 OctPartial week	51	100.0	100.0	53
12 to 18 OctPartial week	47	107.9	95.8	66
19 to 25 OctPartial week	44	126.2	96.9	73
26 to 31 OctPartial week	68	195.4	97.4	105

Sample. Average open roles in Agentic Tasks & RL Environments over each week's days, on the 18 platforms tracked since 1 Oct 2026 (the fixed panel; 9 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; Mindrift on 14 Oct 2026 and 22 Oct 2026; OpenTrain 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), Anyone AI (first tracked 11 Oct 2026), Claru (first tracked 14 Oct 2026), Weekday (first tracked 18 Oct 2026), Innodata (first tracked 18 Oct 2026), Lifted (Upwork) (first tracked 18 Oct 2026), TELUS Digital AI (first tracked 22 Oct 2026), Surge AI (first tracked 22 Oct 2026), Fleet AI (first tracked 22 Oct 2026) and Cohere (first tracked 25 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 2

Listings added and removed

How fast do roles in Agentic Tasks & RL Environments turn over, and is the stock growing on the same platforms?

Work	Open on 1 Oct 2026	Open on 31 Oct 2026, same platforms	Change	New listings	Removed	Median days listed
Agentic Tasks & RL Environments	67	144	+115.5%	89	39	29.8 days
All AI training work	2,665	2,554	-4.2%	1,638	2,018	30.0 days

Sample. Roles listed from 1 Oct 2026 to 31 Oct 2026: 199 in Agentic Tasks & RL Environments, 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 reads on its own (not marked) from 2.7 roles open at the start: the weight of the rest of AI training work's change, fitted on the two.

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; 39 here).

Source. AITraining.jobs Research, The Market for Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 3

Who lists it

Which platforms list roles in Agentic Tasks & RL Environments, and what does each advertise?

Platform	Open roles	Share of open roles	Stating an hourly rate	Median per hour
Mercor	28	22.6%	92.9%	$50
Mindrift	23	18.5%	100.0%	n/a
Turing	16	12.9%	6.3%	n/a
AfterQuery	12	9.7%	100.0%	$80
micro1	11	8.9%	100.0%	$90
SuperAnnotate (SME)	6	4.8%	100.0%	n/a
Anyone AI	5	4.0%	100.0%	$55
Invisible	4	3.2%	100.0%	$60
OpenTrain AI	4	3.2%	100.0%	$30
Alignerr	2	1.6%	100.0%	n/a
Claru	2	1.6%	100.0%	n/a
Innodata	2	1.6%	100.0%	n/a
Terac	2	1.6%	100.0%	n/a
Weekday	2	1.6%	0.0%	n/a
Cohere	1	0.8%	0.0%	n/a
Fleet AI	1	0.8%	100.0%	n/a
Lifted (Upwork)	1	0.8%	0.0%	n/a
Surge AI	1	0.8%	100.0%	n/a
TELUS Digital AI	1	0.8%	100.0%	n/a

Sample. 124 roles in Agentic Tasks & RL Environments open at the end of 31 Oct 2026, by the platform that lists them: HHI 1,270 (unconcentrated), 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 4

What it pays

What do roles in Agentic Tasks & RL Environments advertise per hour, against AI training work as a whole?

Work	Median per hour	Typical pay from	Typical pay to	Stating an hourly rate	Roles stating pay
Agentic Tasks & RL Environments	$65	$45	$120	83.1%	103
All AI training work	$40	$30	$125	81.4%	3,565

Sample. Roles open on 31 Oct 2026: 124 in Agentic Tasks & RL Environments, 103 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 5

How its rates are distributed

What share of roles in Agentic Tasks & RL Environments pay $50 an hour or more?

Advertised rate	Open roles	Share of priced roles	This rate or less	All AI training work
Under $15/hr	5	4.9%	4.9%	6.9%
$15 to $25/hr	10	9.7%	14.6%	10.6%
$25 to $35/hr	10	9.7%	24.3%	11.9%
$35 to $50/hr	19	18.4%	42.7%	26.0%
$50 to $75/hr	29	28.2%	70.9%	14.7%
$75 to $100/hr	25	24.3%	95.1%	15.3%
$100 to $150/hr	4	3.9%	99.0%	9.4%
$150/hr or more	1	1.0%	100.0%	5.1%

Sample. 103 roles in Agentic Tasks & RL Environments 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 6

Applicant demand per open role

Do roles in Agentic Tasks & RL Environments draw more or fewer applicants per opening than the average AI training role?

Roles	Clicks per role a week	Index	Clicks	Avg open roles
Agentic Tasks & RL Environments	1.22	0.36x	390	72
All AI training work	3.41	1.00x	53,794	3,561
Its roles stating an hourly rate	1.39	0.41x	344	56
Its roles stating no hourly rate	0.66	0.19x	46	16
Its roles open worldwideSmall sample	1.58	0.46x	64	9
Its roles limited by countrySmall sample	1.17	0.34x	326	63

Sample. Apply clicks on a specific role on AITraining.jobs, from 1 Oct 2026 to 31 Oct 2026: 390 on roles in Agentic Tasks & RL Environments, 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.

Agentic Tasks & RL Environments 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 38.8 open role-days (5.5 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). Its roles by reach, against each other: Every row is marked as a small sample: the rates of the two sides differ no more than chance makes them, so none reads on its own and none is ranked. 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 7

Applicant demand by listing age

Do newer roles in Agentic Tasks & RL Environments draw more applicants than older ones?

Listing age	Clicks per role a week	Index (this work = 1)	Clicks	Avg open roles
Listed during the window	4.08	3.33x	301	17
Listed up to 4 weeks before it	0.43	0.35x	57	30
Listed 4 to 12 weeks before it	0.28	0.23x	19	15
Listed more than 12 weeks before it	0.17	0.14x	6	8
Listing date unknown	1.10	0.90x	7	1

Sample. Apply clicks on roles in Agentic Tasks & RL Environments, 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 4.9 open role-days (0.7 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 8

Who may apply: location rules

Can people apply to roles in Agentic Tasks & RL Environments from anywhere?

Location rule	Open roles	Share of its open roles	All AI training work
Open worldwide	9	7.3%	18.5%
Worldwide except listed countries	56	45.2%	18.1%
Only listed countries	59	47.6%	63.0%
No rule stated	0	0.0%	0.4%

Sample. 124 roles in Agentic Tasks & RL Environments 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 9

Who may apply: roles open to each country

How many roles in Agentic Tasks & RL Environments can a resident of each country apply to?

Country	Open roles	Share of its open roles	Median per hour
Any country (worldwide roles only)	9	7.3%	$60
United States	84	67.7%	$65
India	80	64.5%	$65
United Kingdom	74	59.7%	$65
Germany	72	58.1%	$60
Indonesia	70	56.5%	$65
Philippines	70	56.5%	$65
Argentina	63	50.8%	$55
Bangladesh	63	50.8%	$55
Colombia	62	50.0%	$55
Chile	61	49.2%	$55
Egypt	61	49.2%	$55
Brazil	60	48.4%	$60
Nigeria	59	47.6%	$55
Ghana	57	46.0%	$55
Japan	55	44.4%	$55
South Korea	55	44.4%	$55
Saudi Arabia	55	44.4%	$55
Pakistan	50	40.3%	$80
Cambodia	30	24.2%	$60
Palestine	25	20.2%	$90

Sample. 124 roles in Agentic Tasks & RL Environments 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 10

What the roles are called

What are roles in Agentic Tasks & RL Environments called: annotator, evaluator, expert or trainer?

Title word	Open roles	Share of its open roles	Median per hour	Platforms
Engineer or developer	42	33.9%	$80	10
Trainer	29	23.4%	$60	3
Expert or SME	20	16.1%	$65	7
Analyst or researcher	18	14.5%	$80	4
Evaluator or reviewer	12	9.7%	$65	8
Specialist	8	6.5%	n/a	5
Lead or manager	6	4.8%	n/a	2
Red teamer or tester	3	2.4%	n/a	3
Annotator or labeler	2	1.6%	n/a	2
Contributor or participant	1	0.8%	n/a	1
Quality assurance	1	0.8%	n/a	1
Writer or editor	1	0.8%	n/a	1

Sample. 101 of the 124 roles in Agentic Tasks & RL Environments open on 31 Oct 2026 name one of these words in their title (81.5%); 12 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 Agentic Tasks & RL Environments Work, October 2026 edition.

Figure 11

What the descriptions ask for

Do roles in Agentic Tasks & RL Environments ask for degrees, credentials, experience or tests?

Requirement	Roles	Share of described roles	All described roles
Mentions a PhD	45	37.5%	17.3%
Mentions a PhD or master's	47	39.2%	25.2%
Mentions any degree	54	45.0%	38.7%
Mentions a professional credential	18	15.0%	16.6%
States years of experience	22	18.3%	26.0%
Asks for 5 years or more	5	4.2%	7.2%
States weekly hours	50	41.7%	24.5%
Mentions an assessment or test	9	7.5%	20.0%
Mentions an AI-led or video interview	8	6.7%	5.0%
Mentions a background check	12	10.0%	0.5%

Sample. 120 roles in Agentic Tasks & RL Environments open on 31 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Claru, Cohere, Fleet AI, Innodata, Invisible, Lifted (Upwork), Mercor, micro1, Mindrift, OpenTrain AI, SuperAnnotate (SME), Surge AI, TELUS Digital AI, Terac, Turing and Weekday), 96.8% 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 Agentic Tasks & RL Environments 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 Agentic Tasks & RL Environments.
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.

Live dataLast 28 complete days, recomputed daily
October 2026 edition (this page)Freezes on first reading
September 2026 editionFrozen 10 Oct 2026
August 2026 editionFrozen 10 Oct 2026

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 Agentic Tasks & RL Environments Work, October 2026 edition. https://aitraining.jobs/research/agentic-rl-environment-market/2026-10

BibTeX

@misc{aitrainingjobs_agentic_rl_environment_market_2026_10,
  author = {{AITraining.jobs}},
  title = {The Market for Agentic Tasks & RL Environments Work, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://aitraining.jobs/research/agentic-rl-environment-market/2026-10}},
}

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