Key findings

1
Egocentric & Wearable Capture drew the most apply clicks: 53 of 187 (28.3%), followed by Embodied-AI Data Annotation (20.3%) and Data & Demonstration Collection (19.8%).
Figure 1
2
Per open role, Embodied-AI Data Annotation drew the most applicant interest: 0.8 apply clicks a week, 11.36x the average role. Egocentric & Wearable Capture drew the least: 0.13 a week (1.81x).
Figure 2
3
A role in its first 7 days drew 0.5 apply clicks a week; a role listed for more than 90 days drew 0.04 (the new role drew 14 times as many).
Figure 4
4
The most-clicked 10% of open roles took 100.0% of apply clicks; 90.2% of the 847 roles open during the window drew none.
Figure 6

Figure 1

Apply clicks by kind of work

Which kinds of robot training work do people apply to?

Kind of work	Apply clicks	Share of clicks	Roles applied to
Egocentric & Wearable Capture	53	28.3%	17
Embodied-AI Data Annotation	38	20.3%	9
Data & Demonstration Collection	37	19.8%	16
Robot Fleet Operations	25	13.4%	13
AV & Drone Operators	14	7.5%	14
Robot Teleoperation	14	7.5%	10
Robot Task Evaluation & QA	6	3.2%	4

Sample. 187 apply clicks on a specific role, from 12 Sep 2026 to 9 Oct 2026.

A further 148 clicks went to an employer's own sign-up page rather than to one role, so they have no kind of work and are not in this figure.

Roles applied to: distinct roles that received at least one of these clicks.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 2

Applicant demand per open role, by kind of work

Which kinds of work are oversubscribed, and which are short of applicants?

Kind of work	Clicks per role a week	Index	Clicks	Avg open roles	Click share	Open-time share
Embodied-AI Data Annotation	0.80	11.36x	38	12	20.3%	1.8%
Data & Demonstration Collection	0.16	2.26x	37	58	19.8%	8.8%
Robot Task Evaluation & QASmall sample	0.13	1.89x	6	11	3.2%	1.7%
Egocentric & Wearable Capture	0.13	1.81x	53	105	28.3%	15.7%
Robot Fleet OperationsSmall sample	0.08	1.07x	25	83	13.4%	12.5%
Robot TeleoperationSmall sample	0.04	0.62x	14	80	7.5%	12.0%
AV & Drone OperatorsSmall sample	0.01	0.16x	14	317	7.5%	47.5%

Sample. 187 apply clicks on 847 roles open at some point from 12 Sep 2026 to 9 Oct 2026.

Clicks per role a week = apply clicks / (days the kind's roles were open / 7). It measures competition for each opening, not the size of the market: a kind with few roles and steady interest reads high.

Index: the kind's rate divided by the rate across all open roles. 2.00x means twice the applicant interest of the average role. Click share and open-time share are the kind's share of all role clicks and of all open role-days.

Rows marked as a small sample have fewer than 30 clicks or fewer than 3 roles open on an average day.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 3

Applicant demand by advertised hourly pay

Do higher-paying roles attract more applicants?

Advertised pay	Clicks per role a week	Index	Clicks	Avg open roles
Under $20/hr	1.86	26.50x	48	6
$20 to $40/hr	0.14	1.94x	40	73
$40 to $60/hrSmall sample	0.55	7.81x	14	6
$60 to $100/hrSmall sample	1.50	21.43x	4	1
No hourly rate stated	0.03	0.50x	81	580

Sample. 187 apply clicks on a specific role, from 12 Sep 2026 to 9 Oct 2026.

Pay is the hourly figure the posting advertises (the middle of a stated range). Roles paid per task or per project with no hourly figure are under 'No hourly rate stated'.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 4

Applicant demand by how long a role has been listed

How quickly does interest in a new role fade?

Listed for	Clicks per role a week	Index	Clicks	Avg open roles
First 7 days	0.50	7.11x	44	22
7 to 30 days	0.15	2.19x	41	67
30 to 90 daysSmall sample	0.02	0.25x	19	273
More than 90 days	0.04	0.51x	42	295
Listing date unknown	1.01	14.45x	41	10

Sample. 187 apply clicks on a specific role, from 12 Sep 2026 to 9 Oct 2026. A role's open days are split across the bands it passed through.

Age runs from the listing date the employer's job board states, or else from the day the role first appeared in the feed. Roles that came in with an employer's back catalogue and state no date are under 'Listing date unknown'.

RobotTraining.jobs ranks recently listed roles higher in its default order, which adds to the first-week figure.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 5

Applicant demand by who can apply

Do roles open worldwide draw more applicants than roles limited to some countries?

Location rule	Clicks per role a week	Index	Clicks	Avg open roles
Open worldwide	1.98	28.18x	37	5
Only listed countries	0.06	0.81x	149	660
No rule statedSmall sample	0.11	1.53x	1	2

Sample. 187 apply clicks on a specific role, from 12 Sep 2026 to 9 Oct 2026.

RobotTraining.jobs shows each visitor the roles open in their country first and hides roles their country cannot apply to unless they choose another country, so roles limited to listed countries are seen by fewer visitors.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 6

How concentrated applicant attention is

Do apply clicks spread across many roles or pile onto a few?

Roles	Number of roles	Share of apply clicks
Most-clicked 1% of roles	9	39.0%
Most-clicked 10%	85	100.0%

Sample. 187 apply clicks on 847 roles open at some point from 12 Sep 2026 to 9 Oct 2026, the roles ranked by the clicks each received (roles with none included).

9.8% of these roles (83) received at least one apply click.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 7

Apply clicks per week

Is applicant activity rising or falling?

Week	Apply clicks	Per day
14 to 20 Sep	32	5
21 to 27 Sep	54	8
28 Sep to 4 Oct	139	20

Sample. All human apply clicks on RobotTraining.jobs, 14 Sep 2026 to 4 Oct 2026, by ISO week (Monday to Sunday, UTC).

Weekly totals grow with RobotTraining.jobs's own audience as well as with the market. To compare kinds of work across weeks, read the shares in the next figure.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Figure 8

Share of apply clicks by kind of work, week by week

Is interest shifting between kinds of work?

Week	Egocentric Capture	Data Annotation	Fleet Operations	Demonstration Collection	Teleoperation	AV & Drone	Other
14 to 20 SepSmall sample	0%	16%	12%	24%	32%	16%	0%
21 to 27 SepSmall sample	13%	25%	21%	21%	8%	8%	4%
28 Sep to 4 Oct	34%	18%	20%	8%	6%	7%	7%

Sample. Apply clicks on a specific role, 14 Sep 2026 to 4 Oct 2026, by ISO week. Each row adds up to 100% (rounded).

Columns are the six kinds of work with the most clicks over the whole period.

Source. RobotTraining.jobs Research, Applicant Demand for Robot Training Work, live data.

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Method and definitions

Apply clicks made on RobotTraining.jobs, joined to the role clicked and the days each role was open. 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.

Apply click: A click on an apply button on RobotTraining.jobs that opens an employer's application page. Made by a person: automated traffic is set aside as it is recorded. Counted per click, not per person.
Role-level click: An apply click on one specific role. Clicks on an employer's or program's general sign-up link are employer-level and have no kind of work, pay or listing age.
Open role-days: For every role, the days of the window it was listed, summed. A role open the whole of a 28-day window adds 28.
Clicks per open role a week: Role-level apply clicks divided by open role-days, times 7.
Demand index: A group's clicks per open role a week divided by the same rate across all open roles. Above 1, the group's roles draw more applicant interest than the average role.
Kind of work: Each role is classified from its title and description into one of the seven kinds of robot training work this site tracks, from robot teleoperation and demonstration collection to egocentric capture, embodied-AI annotation, robot evaluation, fleet operations and AV and drone operation. Every kind links to its own page.
Listing date: The date the employer's job board gives for the posting, or else the first day the role appeared in the feed. A role that arrived with an employer's back catalogue and gives no date has no known listing date.
Location rule: Read from each posting's location text: open worldwide, worldwide except listed countries, only listed countries, or no rule stated.
Window: Live: the last 28 complete days, in UTC. Edition: one calendar month, in UTC.

What this data cannot tell you

Clicks measure interest among the people who use RobotTraining.jobs, not across the whole market.
What is shown first gets clicked more. The default order ranks recently listed roles, roles that state their pay and roles at partner programs higher, and each visitor sees the roles open in their country first.
An apply click starts an application. It is not a submitted application, an acceptance or a hire.
One person can click several roles, so the figures count clicks, not people.

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

Cite and reuse

Free to quote, chart and republish under CC BY 4.0 with a link to this page. Live figures change daily: cite a monthly edition for numbers that will read the same later, or keep the access date.

Citation

RobotTraining.jobs (2026). Applicant Demand for Robot Training Work (live data, 12 Sep 2026 to 9 Oct 2026). https://robottraining.jobs/research/applicant-demand (accessed 10 Oct 2026)

BibTeX

@misc{robottrainingjobs_applicant_demand_live,
  author = {{RobotTraining.jobs}},
  title = {Applicant Demand for Robot Training Work (live data, 12 Sep 2026 to 9 Oct 2026)},
  year = {2026},
  howpublished = {\url{https://robottraining.jobs/research/applicant-demand}},
  note = {Accessed 10 Oct 2026},
}

Data: all figures as CSV (one line per value) or JSON. Every figure also downloads on its own. More open data: datasets and API.

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