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Research ยท October 2026 edition

Robot Training Job Lifespans: How Long Listings Last

Among robot training roles listed from 14 Sep 2026 to 31 Oct 2026, half were gone within 36.4 days of posting; Robot Fleet Operations had the quickest turnover (median 34.2 days), and a median from removed roles alone would read only 22.3 days.

Read the month's story: Robot Training Jobs in October 2026: The Month in Data

Not final yet. The month has ended, yet stragglers in the data may still land up to 3 Nov 2026; after that the edition is locked permanently.

Period
14 Sep 2026 to 31 Oct 2026
48 days, UTC
Calculated
1 Nov 2026, 06:05 UTC
Settles when locked
Where it comes from
Daily reads, starting 12 Sep 2026, of the public job boards run by the robot training employers and programs this site follows.
Method
Revision 3. Terms defined
CC BY 4.0, citing this report

Each figure here comes as CSV and JSON files, emailed to your work address.

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What the data shows

  1. 1

    Of the 195 robot training roles listed from 14 Sep 2026 to 31 Oct 2026, half were taken down within 36.4 days of posting (Kaplan-Meier median); after four weeks, 68.7% were still up.

    Figure 1
  2. 2

    A median built from removed roles alone comes to 22.3 days; add back the 75.4% that are still up and it is 36.4 days, 63.0% longer.

    Figure 4
  3. 3

    The quickest turnover is in Robot Fleet Operations (half gone within 34.2 days, 71.9% still up at four weeks). AV & Drone Operators lasts longest: 88.9% of its roles were still up four weeks after posting.

    Figure 2
  4. 4

    Among employers, micro1 pulls roles soonest (half gone within 12 days, 8.3% still up at four weeks), while Aurora Innovation keeps them up longest (100.0% still up at four weeks).

    Figure 3
  5. 5

    Some apparent turnover is just reposting: 8.3% of removed roles were followed by a fresh listing with the same title from the same employer at a later date.

    Figure 3
  6. 6

    On 1 Nov 2026, 720 of 1,150 open roles (62.6%) had been up for 47 days or longer, past the point where even the longest-lasting listings usually come down. Egocentric & Wearable Capture had the highest share, at 88.8% of its open roles.

    Figure 5

Figure 1

Week by week: the share of listings still up

Of the robot training roles posted, what share is still up one, two, four or eight weeks later?

Age of the listingStill listed
After 1 week
92.8%
148137
After 2 weeks
88.7%
9177
After 3 weeks
79.6%
9071
After 4 weeks
68.7%
5945
After 6 weeks
28.7%
114
After 8 weeksPartial week
n/a
00

Base: 195 roles with a known listing date, listed from 14 Sep 2026 to 31 Oct 2026; 48 had come down by 1 Nov 2026. Back catalogues are excluded.

Method: Kaplan-Meier. A removed role's life ends on the last day the feed showed it. A role that is still up stays in the count for every day it has been observed, then drops out without counting as a removal.

Ages are measured in hours from the posting date on the job board, or from the role's first day in the feed when that came earlier or no date is given. When the first sighting comes more than 2 days after the posting date, the feed was slow to show the role, so it only enters the count at the age it was first seen. A gap of 2 days or less is just the daily read catching up, and the role counts from the day it was posted.

Each share rests on the roles posted at least that long before 1 Nov 2026, and the count of those roles sits next to it. An age that no role in the group has reached yet shows n/a.

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 2

Listing lifetimes by kind of work

Which kinds of robot training work come down quickest, and which stay up the longest?

Kind of workStill listed after 2 weeksAfter 4 weeksMedian lifetime (days)
All kinds of work19588.7%
68.7%
n/a36.4
AV & Drone Operators8092.9%
88.9%
n/an/a
Robot Fleet Operations7598.5%
71.9%
n/a34.2
Data & Demonstration Collection1388.9%
66.7%
n/an/a
Robot Task Evaluation & QASmall sample250.0%
50.0%
n/an/a
Robot TeleoperationSmall sample744.4%
44.4%
n/a6.6
Embodied-AI Data AnnotationSmall sample887.5%
29.2%
n/a26.0
Egocentric & Wearable CaptureSmall sample100.0%
0.0%
n/a12.0

Base: 195 roles with a known listing date, listed from 14 Sep 2026 to 31 Oct 2026, grouped by their classified kind of work.

Both the shares and the median lifetime come from Kaplan-Meier estimates: a role that is still up counts for every day it has been observed.

An n/a median lifetime has one of two causes. Either over half the group's roles were still up at the oldest age the data reaches, so the median lies beyond what has been observed, or fewer than 3 of its roles were posted early enough to read it (no median here rests on fewer). A share shows n/a when none of the group's roles was posted that long ago.

A kind of work whose roles add up to fewer than 176 days of observed listing time gets a small-sample flag and no rank. Below that, the removal pace shared by all kinds of work tells more about it than its own removals do; how much weight that shared pace carries is fitted from the removals themselves.

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 3

Listing lifetimes by employer

Which employers take their robot training roles down soonest?

EmployerStill listed after 2 weeksAfter 4 weeksMedian lifetime (days)
TSMG35100.0%
100.0%
n/an/an/a
Avride31100.0%
79.3%
n/a34.20.0%
Tesla31n/a
n/a
n/an/an/a
micro11849.7%
8.3%
n/a12.00.0%
Amazon Prime AirSmall sample10100.0%
n/a
n/an/a100.0%
Aurora Innovation8100.0%
100.0%
n/a31.466.7%
Serve Robotics7100.0%
75.0%
n/an/a0.0%
Wayve683.3%
66.7%
n/an/a0.0%
Anduril Industries4100.0%
75.0%
n/an/a0.0%
Collaborative Robotics3100.0%
100.0%
n/an/an/a
Genesis AI3100.0%
100.0%
n/an/an/a
Kodiak AISmall sample366.7%
66.7%
n/an/a0.0%
MotionalSmall sample366.7%
66.7%
n/an/a100.0%
Torc RoboticsSmall sample3n/a
n/a
n/an/a0.0%
TransdevSmall sample3n/a
n/a
n/an/an/a
WaymoSmall sample366.7%
66.7%
n/an/a0.0%
Figure AISmall sample20.0%
0.0%
n/an/a0.0%
MonumentalSmall sample2100.0%
n/a
n/an/an/a
MooveSmall sample2n/a
n/a
n/an/an/a
Nimble RoboticsSmall sample250.0%
50.0%
n/an/a0.0%
Shield AISmall sample2n/a
100.0%
n/an/an/a
SymboticSmall sample2n/a
n/a
n/an/an/a
DexorySmall sample1100.0%
100.0%
n/an/an/a
Dyna RoboticsSmall sample1n/a
n/a
n/an/an/a
HumanoidSmall sample1100.0%
100.0%
n/an/an/a
Keywords StudiosSmall sample1n/a
n/a
n/an/an/a
Mind RoboticsSmall sample1n/a
n/a
n/an/an/a
NuroSmall sample1100.0%
n/a
n/an/an/a
Skild AISmall sample10.0%
0.0%
n/an/a0.0%
Stack AVSmall sample1100.0%
n/a
n/an/an/a
Tutor IntelligenceSmall sample1n/a
n/a
n/an/an/a
VaySmall sample1100.0%
100.0%
n/an/an/a
Welo DataSmall sample1n/a
n/a
n/an/an/a
ZooxSmall sample1n/a
n/a
n/an/a0.0%

Base: 195 roles with a known listing date, listed from 14 Sep 2026 to 31 Oct 2026, grouped by the employer posting them. Based on listings alone.

An n/a median lifetime has one of two causes. Either over half the group's roles were still up at the oldest age the data reaches, so the median lies beyond what has been observed, or fewer than 3 of its roles were posted early enough to read it (no median here rests on fewer). A share shows n/a when none of the group's roles was posted that long ago.

Re-listed means a removed role whose title the same employer listed again at a later date (the gaps between a removal and the next listing with that title form one kind only, so every such listing counts whatever the gap). The column is filled only for employers with enough removed roles to read on their own: 0.9 or more removed roles, a weight fitted from the employers' own counts. Across the cohort, 8.3% of removed roles were re-listed this way. An employer that pulls roles and reposts them, say every week, shows short lifetimes here even if the job itself stays open for months. Listings are counted exactly as the feeds publish them, with no further merging.

Where an employer posts a separate listing for each city or country, every one of them gets its own lifetime.

A employer whose roles add up to fewer than 68 days of observed listing time gets a small-sample flag and no rank. Below that, the removal pace shared by all employers tells more about it than its own removals do; how much weight that shared pace carries is fitted from the removals themselves.

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 4

Counting only removed roles gives too short a median

By how much does a median built only from removed roles understate how long listings really stay up?

Kind of workStill listed on 1 Nov 2026Median days, removed roles onlyMedian lifetime, all roles (days)
All kinds of work19575.4%22.3
36.4
AV & Drone Operators8091.3%19.4
n/a
Data & Demonstration Collection1376.9%27.0
n/a
Robot Fleet Operations7566.7%29.1
34.2

Base: Same cohort: 195 roles listed from 14 Sep 2026 to 31 Oct 2026. Only kinds of work whose lifetimes can be read on their own are shown, as in the chart by kind of work.

Removed roles only: take the roles that have already come down and find the median number of days from posting to last sighting. This is the number a hiring report gives as 'median days listed'. It ignores every role still up, and those are the ones that last longest, so the figure runs short. The more roles still up, the bigger the gap.

All roles: the Kaplan-Meier median. Every role still up is included for each day it has been observed.

An n/a median lifetime has one of two causes. Either over half the group's roles were still up at the oldest age the data reaches, so the median lies beyond what has been observed, or fewer than 3 of its roles were posted early enough to read it (no median here rests on fewer). A share shows n/a when none of the group's roles was posted that long ago.

The removed-only median is shown only when a group has 3 or more removed roles, the fewest any median here rests on.

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 5

Evergreen roles, still up past the normal life of a listing

Of the roles open right now, how many were first posted 47 days or more ago?

Kind of workListed 47+ daysShare of open roles
All kinds of work1,150720
62.6%
101
Egocentric & Wearable Capture134119
88.8%
101
Robot Teleoperation8267
81.7%
119
Robot Task Evaluation & QA97
77.8%
73
AV & Drone Operators544369
67.8%
117
Data & Demonstration Collection12756
44.1%
17
Robot Fleet Operations23796
40.5%
31
Embodied-AI Data Annotation176
35.3%
29

Base: All 1,150 roles open on 1 Nov 2026, whatever their listing date, back catalogues counted in.

A role counts as evergreen when it is still open on 1 Nov 2026 and was posted 47 days or more earlier. Past that age even a listing of the longest-lasting kind is more likely to have come down than to still be up. The cut-off comes from fitting the lifetimes of the 195 roles listed from 14 Sep 2026 to 31 Oct 2026 as a mix of 1 kind: the longest-lasting kind holds 100.0% of them and stays up 67.3 days on average, so a role open beyond the cut-off is being kept open on purpose.

When a back-catalogue role has no posting date on its board, its age starts on the first day this site saw it. Its true age may be higher, so both that age and the evergreen count are minimums.

A row with under 5.9 open roles carries a small-sample mark and is left unranked: under that count, the average across all rows says more than the row's own open roles do (a weight fitted on the counts themselves).

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 6

Weekly churn: open roles that come down

Each week, what share of open robot training roles is taken down?

WeekShare removed in the weekOpen when the week began
14 to 20 SepPartial week
2.2%
647149
21 to 27 SepPartial week
3.9%
6422521
28 Sep to 4 OctPartial week
3.8%
6882630
5 to 11 OctPartial week
2.0%
6931447
12 to 18 OctPartial week
2.5%
746198
19 to 25 OctPartial week
2.5%
1,0262675

Base: Each full ISO week (Monday through Sunday, UTC) between 14 Sep 2026 and 31 Oct 2026, counting only employers that were already tracked when the week began.

Churn takes the roles open at 00:00 UTC on Monday and asks what share were seen for the last time that week and had left the feed by the end of the observation. A role posted and pulled inside the same week is left out of the rate and counted under new listings instead.

A week only includes employers whose tracking started before it, so bringing a new employer into the dataset cannot show up as churn or growth.

When one employer pulls many roles at once, for instance because a project ended or its board was reorganised, that week stands out as a spike.

A row with under 2571 roles open at the week's start carries a small-sample mark and is left unranked: under that count, the average across all rows says more than the row's own roles open at the week's start do (a weight fitted on the counts themselves).

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

Figure 7

Do roles that draw applicants in their first week come down sooner?

Once a robot training role has been up a week, does it come down sooner when people tried to apply to it in that week?

In its first week hereRoles still up at one weekStill up 2 weeks later4 weeks laterMedian lifetime (days from posting)
Someone clicked apply on it hereSmall sample25772.3%
56.4%
n/a
Nobody clicked apply on it hereSmall sample1042096.2%
55.4%
36.4

Base: 129 of the roles listed from 14 Sep 2026 to 31 Oct 2026 that were still up one week after posting, first seen on their posting day and posted after this site began logging apply clicks (18 Sep 2026).

Landmark method: each role's life is read from the end of its first week onward, so a role cannot be counted as attracting applicants just because it stayed up longer. Kaplan-Meier, as in the other figures.

Apply clicks are human clicks on this site's apply buttons for that role (automated traffic left out); employers see applicants from many places, so this measures attention from this site's visitors, not a role's whole demand. A role coming down is not proof that it was filled.

Every group gets a small-sample flag and none is ranked: the groups take roles down at paces no further apart than chance alone would produce.

Credit: RobotTraining.jobs Research, Robot Training Job Lifespans: How Long Listings Last, October 2026 edition.

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    Every role on 100 employer job boards, read each day since 12 Sep 2026: its pay, its place, and the first and last day it was up.

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How it was measured

Daily reads, starting 12 Sep 2026, of the public job boards run by the robot training employers and programs this site follows. A single database query produces each figure for the window shown, and the live page and every monthly edition run that identical query. The note under each figure gives its base.

Listing date
The posting date the employer's job board shows, or, failing that, the first day the role turned up in the feed. A role that came in with an employer's back catalogue and carries no date has no known listing date.
Cohort
All roles with a known listing date posted in the 26 weeks up to the end of the period, none earlier than 14 Sep 2026 (when this site's index begins). Each employer's back catalogue, meaning whatever it already had up in its first week in this dataset, is left out.
Lifetime
Measured in hours and shown in days, from the listing date to the role's final sighting in its employer's feed. A role still up when the period ends has lived at least that long, so it is treated as censored rather than removed.
Still listed after N weeks
A Kaplan-Meier estimate of what share of roles remain in their feed N weeks past their listing date. Each role contributes for as long as it has been observed, which stops roles that are still up from passing for short-lived ones. If a role was first spotted more than two days after its listing date, it surfaced late and is counted only from the age at which it was spotted.
Median lifetime
The estimated age at which half of all roles have been taken down. If more than half are still up at the oldest age the data reaches, the median has not been reached yet.
Removed-only median
The familiar 'median days listed': days from posting to last sighting, for roles already taken down. Because it ignores roles still up (the longer-lived ones), it comes out shorter than the median lifetime.
Re-listed
A role that came down and later reappeared under the same title at the same employer inside the reposting window. That window comes from the gaps between a removal and the next listing with the same title, split into kinds (most removed roles never return): a gap counts while it is likelier to belong to the shortest kind, an employer putting the same role up again, than to any longer kind, a fresh opening that happens to share the title.
Evergreen role
A role still open when the period ends that is older than the age at which even the longest-lived kind of listing is more likely gone than up. The cohort's lifetimes are fitted as a mix of kinds, each with its own daily chance of coming down, and the cut-off is the first whole day t at which q to the power t is one half or less, q being the longest-lived kind's daily chance of staying up.
Weekly churn
Take the roles open at 00:00 UTC on Monday at employers followed before that week; churn is the share of them taken down by the end of the ISO week.
Kind of work
A role's title and description place it in one of the seven kinds of robot training work this site follows, ranging from robot teleoperation and demonstration collection through egocentric capture, embodied-AI annotation, robot evaluation and fleet operations to AV and drone operation. Each kind has a page of its own.
Window
Live page: roles posted in the 26 weeks to yesterday (UTC), none before 14 Sep 2026. Edition: roles posted in the 26 weeks to month end, none before 14 Sep 2026, followed up to that month end.

Limits of this data

  • Hiring that happens without a public job board is not captured.
  • A posting does not equal a hire, and a role that comes down may have been filled, put on hold or cancelled; employers do not say which.
  • A brief listing life does not always mean a brief opening: some employers pull a role and repost it, or post one copy per city. The re-listing column flags where this happens.
  • Feeds are read roughly once a day. A role that goes up and comes down between reads can be missed, and each removal is dated to the final read that still showed it.
  • No estimate is made past the longest age the cohort has actually been watched, so while the dataset is young the later ages read n/a.
  • When an employer pulls many roles at once (a project wraps up, a board gets reorganised), it shows up as one spike in weekly churn.

Collection and classification of listings are explained on the methodology page. Freshness, completeness and consistency are tested daily in the data quality report.

Monthly editions

The live page tracks each role listed in the 26 weeks up to yesterday (none earlier than 14 Sep 2026) and updates daily. Every finished month also gets its own edition, locked two days after month end, so a number quoted from it stays fixed.

  • Live pageAll roles of the last 26 weeks, rebuilt daily
  • October 2026 edition (you are here)Will lock when the next daily refresh runs

Quoting this report

You may quote, chart or republish these figures under CC BY 4.0, provided you link back to this page. This edition is locked: its numbers will not change.

Citation

RobotTraining.jobs (2026). Robot Training Job Lifespans: How Long Listings Last, October 2026 edition. https://robottraining.jobs/research/how-long-robot-training-roles-stay-open/2026-10

BibTeX

@misc{robottrainingjobs_how_long_robot_training_roles_stay_open_2026_10,
  author = {{RobotTraining.jobs}},
  title = {Robot Training Job Lifespans: How Long Listings Last, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://robottraining.jobs/research/how-long-robot-training-roles-stay-open/2026-10}},
}
Files: every figure in one CSV (a row per value) or as JSON, emailed to your work address.Other open data: datasets and API

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