Key findings
- 1
Rating or scoring responses against guidelines is the task mentioned most often, in 38.3% of the 3,260 roles read, ahead of annotating, labelling or tagging data (36.1%).
- 3
The median role read mentions 3 different tasks; 55.4% mention three or more, and 5.0% name none.
- 4
The highest share in any kind of work is reviewing for safety or policy in Red-Teaming & AI Safety: 88.9% of its roles read mention it, against 6.3% of all roles read.
- 5
Among tasks with at least 8 priced roles on 2 or more platforms, roles mentioning taking part in surveys or studies advertise the highest median ($100/hr) and roles mentioning transcribing audio or video the lowest ($25/hr), against $65/hr for all roles read.
- 6
The platforms differ most on annotating, labelling or tagging data: 100.0% of Sigma AI's roles read mention it, against 0.0% at Anyone AI.
- 7
Beyond judging and authoring, 19.9% of roles read mention recording or transcribing audio and video, 9.9% writing or reviewing code, and 2.9% red-teaming or adversarial testing.
Figure 1
Tasks AI training roles describe
What do AI training roles ask people to do?
| Task | Roles mentioning it | Share of roles read |
|---|---|---|
| Rate or score responses against guidelines | 1,248 | 38.3% |
| Annotate, label or tag data | 1,177 | 36.1% |
| Create evaluation tasks, benchmarks or test cases | 853 | 26.2% |
| Fact-check or verify accuracy | 793 | 24.3% |
| Write prompts or questions | 761 | 23.3% |
| Translate or localise | 636 | 19.5% |
| Give feedback on reasoning or explanations | 476 | 14.6% |
| Record audio, video or photos | 474 | 14.5% |
| Write ideal responses or demonstrations | 429 | 13.2% |
| Solve problems step by step | 415 | 12.7% |
| Hold conversations or sessions | 388 | 11.9% |
| Compare or rank model responses | 326 | 10.0% |
| Edit or rewrite text | 315 | 9.7% |
| Transcribe audio or video | 284 | 8.7% |
| Take part in surveys or studies | 270 | 8.3% |
| Review or debug code | 263 | 8.1% |
| Review agent trajectories or tool use | 216 | 6.6% |
| Review for safety or policy | 207 | 6.3% |
| Write code or tests | 207 | 6.3% |
| Write rationales for judgments | 184 | 5.6% |
| Write rubrics, criteria or guidelines | 163 | 5.0% |
| Review others' work (QA) | 140 | 4.3% |
| Red-team, jailbreak or adversarial testing | 96 | 2.9% |
| Do hands-on professional work (models, analyses, simulations) | 81 | 2.5% |
| Perform physical tasks for robot data | 15 | 0.5% |
Sample. 3,260 roles open on 17 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Handshake AI, Invisible, Mercor, micro1, Mindrift, OneForma, OpenTrain AI, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, RemoExperts, Remotasks, Sigma AI, Sovrano AI, SuperAnnotate (SME), Terac, TransPerfect DataForce, Turing, Vetto, Welo Data and xAI (SpaceXAI)), 88.9% of the 3,668 open roles; the boards that publish descriptions are expert networks, so these roles lean towards expert work.
A role mentions a task when its description contains one of the task's documented patterns, anywhere in the text: a mention is not necessarily the main task, and a role often mentions several.
Hiring steps are not tasks: a description saying applications are read against a rubric, or that applying starts with an AI interview, does not count as writing rubrics or holding conversations.
Source. AITraining.jobs Research, What AI Trainers Do, live data.
Figure 2
Tasks by kind of work
Which tasks does each kind of AI training work involve?
| Task | Domain Experts (992) | Multilingual (967) | Transcription & Audio (408) | Coding (239) | Math & STEM (200) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rate or score responses against guidelines | 54% | 34% | 10% | 48% | 27% | 47% | 42% | 32% | 0% | 67% | 0% | 67% |
| Annotate, label or tag data | 26% | 45% | 48% | 29% | 12% | 47% | 64% | 19% | 10% | 58% | 6% | 48% |
| Create evaluation tasks, benchmarks or test cases | 46% | 7% | 7% | 34% | 51% | 30% | 24% | 34% | 2% | 36% | 6% | 26% |
| Fact-check or verify accuracy | 24% | 31% | 1% | 38% | 38% | 27% | 9% | 14% | 2% | 28% | 3% | 48% |
| Write prompts or questions | 29% | 23% | 1% | 36% | 39% | 28% | 8% | 24% | 0% | 36% | 0% | 56% |
| Translate or localise | 1% | 52% | 17% | 2% | 3% | 7% | 25% | 3% | 2% | 3% | 0% | 11% |
| Give feedback on reasoning or explanations | 23% | 7% | 0% | 26% | 32% | 26% | 2% | 9% | 0% | 14% | 0% | 30% |
| Record audio, video or photos | 2% | 14% | 51% | 6% | 0% | 2% | 18% | 41% | 84% | 0% | 28% | 0% |
| Write ideal responses or demonstrations | 25% | 6% | 0% | 21% | 16% | 13% | 4% | 5% | 0% | 47% | 0% | 26% |
| Solve problems step by step | 10% | 16% | 1% | 18% | 45% | 8% | 3% | 2% | 0% | 0% | 0% | 7% |
| Hold conversations or sessions | 7% | 16% | 11% | 14% | 34% | 5% | 2% | 2% | 0% | 8% | 6% | 0% |
| Compare or rank model responses | 11% | 10% | 0% | 20% | 2% | 26% | 5% | 7% | 0% | 39% | 0% | 37% |
| Edit or rewrite text | 5% | 20% | 5% | 4% | 3% | 12% | 3% | 7% | 0% | 3% | 0% | 48% |
| Transcribe audio or video | 0% | 13% | 37% | 0% | 0% | 0% | 6% | 0% | 8% | 0% | 0% | 0% |
| Take part in surveys or studies | 1% | 24% | 1% | 1% | 0% | 3% | 1% | 2% | 2% | 3% | 56% | 4% |
| Review or debug code | 3% | 2% | 0% | 78% | 3% | 9% | 3% | 17% | 0% | 3% | 6% | 0% |
| Review agent trajectories or tool use | 10% | 2% | 2% | 9% | 5% | 14% | 6% | 25% | 14% | 6% | 6% | 11% |
| Review for safety or policy | 9% | 4% | 0% | 6% | 1% | 10% | 9% | 0% | 0% | 89% | 0% | 15% |
| Write code or tests | 4% | 0% | 1% | 49% | 5% | 7% | 0% | 22% | 2% | 11% | 6% | 4% |
| Write rationales for judgments | 8% | 4% | 0% | 7% | 2% | 17% | 9% | 2% | 0% | 22% | 0% | 22% |
| Write rubrics, criteria or guidelines | 10% | 0% | 7% | 3% | 5% | 4% | 2% | 7% | 0% | 6% | 0% | 11% |
| Review others' work (QA) | 5% | 0% | 11% | 10% | 3% | 5% | 2% | 5% | 2% | 11% | 0% | 4% |
| Red-team, jailbreak or adversarial testing | 4% | 1% | 0% | 1% | 1% | 8% | 0% | 2% | 0% | 78% | 3% | 0% |
| Do hands-on professional work (models, analyses, simulations) | 6% | 0% | 0% | 2% | 5% | 2% | 3% | 3% | 0% | 0% | 0% | 0% |
| Perform physical tasks for robot data | 0% | 0% | 0% | 0% | 0% | 0% | 3% | 0% | 25% | 0% | 0% | 0% |
Sample. 3,260 roles open on 17 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Handshake AI, Invisible, Mercor, micro1, Mindrift, OneForma, OpenTrain AI, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, RemoExperts, Remotasks, Sigma AI, Sovrano AI, SuperAnnotate (SME), Terac, TransPerfect DataForce, Turing, Vetto, Welo Data and xAI (SpaceXAI)), 88.9% of the 3,668 open roles; the boards that publish descriptions are expert networks, so these roles lean towards expert work. Kinds of work with at least 10 roles read; each cell is the share of that kind's roles read that mention the task (roles read in the column header).
A role mentions a task when its description contains one of the task's documented patterns, anywhere in the text: a mention is not necessarily the main task, and a role often mentions several.
Every kind of work with a role read is shown.
Source. AITraining.jobs Research, What AI Trainers Do, live data.
Figure 3
Advertised pay of roles mentioning each task
Which tasks come with the highest advertised pay?
| Task | Median per hour | Middle half | Roles stating pay |
|---|---|---|---|
| Take part in surveys or studies | $100 | $100 to $100 | 257 |
| Perform physical tasks for robot data | $95 | $14 to $108 | 11 |
| Review others' work (QA) | $80 | $63 to $100 | 80 |
| Do hands-on professional work (models, analyses, simulations) | $69 | $43 to $90 | 66 |
| Write ideal responses or demonstrations | $68 | $39 to $92 | 362 |
| Hold conversations or sessions | $65 | $65 to $65 | 348 |
| Create evaluation tasks, benchmarks or test cases | $65 | $40 to $85 | 689 |
| Fact-check or verify accuracy | $65 | $36 to $65 | 752 |
| Review or debug code | $65 | $50 to $75 | 220 |
| Solve problems step by step | $65 | $65 to $65 | 370 |
| Write code or tests | $65 | $55 to $83 | 148 |
| Write prompts or questions | $65 | $40 to $65 | 700 |
| Write rubrics, criteria or guidelines | $65 | $36 to $90 | 149 |
| Rate or score responses against guidelines | $60 | $35 to $85 | 1,141 |
| Red-team, jailbreak or adversarial testing | $60 | $42 to $79 | 63 |
| Give feedback on reasoning or explanations | $55 | $40 to $80 | 454 |
| Review for safety or policy | $51 | $29 to $70 | 174 |
| Write rationales for judgments | $45 | $18 to $73 | 132 |
| Compare or rank model responses | $44 | $25 to $70 | 304 |
| Annotate, label or tag data | $37 | $25 to $65 | 853 |
| Edit or rewrite text | $36 | $25 to $43 | 295 |
| Review agent trajectories or tool use | $35 | $20 to $55 | 119 |
| Translate or localise | $34 | $20 to $45 | 446 |
| Record audio, video or photos | $30 | $20 to $40 | 258 |
| Transcribe audio or video | $25 | $14 to $31 | 96 |
Sample. 3,260 roles open on 17 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Handshake AI, Invisible, Mercor, micro1, Mindrift, OneForma, OpenTrain AI, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, RemoExperts, Remotasks, Sigma AI, Sovrano AI, SuperAnnotate (SME), Terac, TransPerfect DataForce, Turing, Vetto, Welo Data and xAI (SpaceXAI)), 88.9% of the 3,668 open roles; the boards that publish descriptions are expert networks, so these roles lean towards expert work. 2,626 of the 3,260 roles read state an hourly rate (median $65/hr).
A role mentions a task when its description contains one of the task's documented patterns, anywhere in the text: a mention is not necessarily the main task, and a role often mentions several.
Pay is the hourly figure the posting advertises (the middle of a stated range). Medians need 8 roles stating a rate from at least 2 platforms; others are marked and listed after the ranked tasks. The middle half runs from the 25th to the 75th percentile; 1.00x is the median of all roles read.
A role mentioning several tasks counts in each, and tasks travel with kinds of work and seniority: a pay difference is an association, not the price of the task.
Source. AITraining.jobs Research, What AI Trainers Do, live data.
Figure 4
Tasks by platform
How do the platforms that publish descriptions differ in the work they describe?
| Task | AfterQuery (216) | Anyone AI (128) | Appen (55) | Babel Audio (43) | Braintrust (78) | Claru (42) | Handshake AI (170) | Invisible (532) | Mercor (229) | micro1 (248) | Mindrift (297) | OneForma (24) | OpenTrain AI (42) | Outlier (Scale AI) (5) | Pasiflora AI (7) | Perle Labs (67) | Pila8 (3) | RemoExperts (36) | Remotasks (3) | Sigma AI (90) | Sovrano AI (20) | SuperAnnotate (SME) (377) | Terac (22) | TransPerfect DataForce (66) | Turing (190) | Vetto (20) | Welo Data (235) | xAI (SpaceXAI) (15) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rate or score responses against guidelines | 57% | 20% | 0% | 0% | 46% | 14% | 94% | 32% | 31% | 38% | 1% | 13% | 45% | 20% | 57% | 0% | 0% | 61% | 67% | 0% | 20% | 91% | 27% | 3% | 42% | 25% | 31% | 0% |
| Annotate, label or tag data | 9% | 0% | 31% | 47% | 44% | 36% | 10% | 30% | 29% | 27% | 5% | 25% | 41% | 0% | 57% | 91% | 0% | 28% | 0% | 100% | 20% | 89% | 14% | 12% | 53% | 10% | 37% | 100% |
| Create evaluation tasks, benchmarks or test cases | 63% | 90% | 0% | 0% | 33% | 2% | 42% | 7% | 48% | 23% | 11% | 4% | 41% | 0% | 0% | 0% | 0% | 33% | 0% | 0% | 75% | 11% | 46% | 3% | 64% | 15% | 12% | 87% |
| Fact-check or verify accuracy | 2% | 2% | 0% | 0% | 31% | 5% | 2% | 63% | 4% | 11% | 0% | 0% | 2% | 0% | 0% | 0% | 0% | 3% | 67% | 0% | 5% | 83% | 14% | 2% | 25% | 5% | 7% | 0% |
| Write prompts or questions | 17% | 2% | 0% | 0% | 12% | 2% | 35% | 60% | 11% | 7% | 1% | 4% | 26% | 0% | 0% | 0% | 0% | 11% | 33% | 0% | 0% | 56% | 9% | 6% | 23% | 0% | 5% | 0% |
| Translate or localise | 1% | 1% | 2% | 0% | 33% | 0% | 0% | 28% | 4% | 4% | 0% | 29% | 10% | 0% | 0% | 70% | 0% | 0% | 33% | 92% | 0% | 31% | 0% | 9% | 19% | 5% | 55% | 33% |
| Give feedback on reasoning or explanations | 6% | 35% | 0% | 0% | 26% | 10% | 7% | 4% | 11% | 8% | 4% | 4% | 10% | 0% | 0% | 2% | 0% | 17% | 0% | 0% | 0% | 71% | 18% | 0% | 10% | 10% | 0% | 0% |
| Record audio, video or photos | 21% | 0% | 64% | 7% | 33% | 62% | 0% | 6% | 19% | 5% | 0% | 25% | 5% | 80% | 14% | 12% | 100% | 19% | 0% | 90% | 5% | 9% | 5% | 46% | 6% | 0% | 19% | 100% |
| Write ideal responses or demonstrations | 43% | 6% | 0% | 0% | 22% | 5% | 1% | 0% | 20% | 8% | 14% | 4% | 12% | 0% | 57% | 0% | 0% | 39% | 33% | 0% | 10% | 36% | 5% | 3% | 18% | 15% | 0% | 0% |
| Solve problems step by step | 3% | 0% | 0% | 0% | 1% | 5% | 1% | 60% | 4% | 5% | 0% | 0% | 7% | 0% | 0% | 2% | 0% | 3% | 0% | 0% | 5% | 4% | 9% | 0% | 21% | 10% | 1% | 0% |
| Hold conversations or sessions | 0% | 0% | 2% | 5% | 0% | 2% | 0% | 61% | 2% | 0% | 0% | 17% | 0% | 20% | 0% | 8% | 67% | 0% | 0% | 0% | 0% | 0% | 0% | 26% | 5% | 10% | 6% | 0% |
| Compare or rank model responses | 3% | 2% | 0% | 0% | 21% | 7% | 7% | 0% | 5% | 3% | 0% | 0% | 5% | 0% | 57% | 0% | 0% | 17% | 67% | 0% | 10% | 56% | 5% | 0% | 17% | 5% | 3% | 0% |
| Edit or rewrite text | 1% | 0% | 6% | 0% | 30% | 2% | 1% | 14% | 0% | 13% | 1% | 4% | 7% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 37% | 0% | 3% | 8% | 10% | 5% | 0% |
| Transcribe audio or video | 1% | 0% | 27% | 47% | 3% | 7% | 1% | 0% | 7% | 8% | 0% | 8% | 19% | 0% | 0% | 91% | 0% | 0% | 0% | 99% | 0% | 0% | 0% | 5% | 1% | 0% | 13% | 87% |
| Take part in surveys or studies | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 2% | 0% | 82% | 4% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 5% | 1% | 68% | 3% | 0% | 0% | 0% | 0% |
| Review or debug code | 8% | 23% | 0% | 0% | 9% | 5% | 1% | 7% | 6% | 9% | 0% | 0% | 7% | 0% | 0% | 0% | 0% | 17% | 0% | 0% | 5% | 16% | 23% | 3% | 27% | 5% | 0% | 0% |
| Review agent trajectories or tool use | 0% | 5% | 0% | 0% | 3% | 19% | 0% | 1% | 10% | 1% | 15% | 0% | 12% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 5% | 5% | 18% | 0% | 52% | 0% | 0% | 0% |
| Review for safety or policy | 1% | 0% | 0% | 0% | 1% | 10% | 5% | 1% | 16% | 3% | 0% | 4% | 10% | 0% | 57% | 0% | 0% | 0% | 0% | 0% | 15% | 28% | 0% | 3% | 8% | 10% | 2% | 0% |
| Write code or tests | 8% | 22% | 0% | 0% | 6% | 7% | 2% | 1% | 5% | 11% | 1% | 0% | 12% | 0% | 0% | 8% | 0% | 11% | 0% | 2% | 30% | 7% | 23% | 0% | 25% | 10% | 1% | 0% |
| Write rationales for judgments | 2% | 0% | 0% | 0% | 1% | 12% | 8% | 0% | 13% | 11% | 4% | 4% | 7% | 0% | 43% | 0% | 0% | 11% | 0% | 0% | 10% | 5% | 0% | 3% | 15% | 30% | 9% | 0% |
| Write rubrics, criteria or guidelines | 1% | 0% | 0% | 0% | 0% | 0% | 0% | 8% | 22% | 11% | 0% | 0% | 5% | 0% | 0% | 0% | 0% | 17% | 0% | 0% | 75% | 1% | 5% | 2% | 7% | 0% | 0% | 0% |
| Review others' work (QA) | 5% | 13% | 0% | 0% | 4% | 2% | 0% | 0% | 8% | 2% | 0% | 0% | 0% | 0% | 0% | 69% | 0% | 17% | 0% | 0% | 10% | 4% | 5% | 0% | 7% | 0% | 1% | 0% |
| Red-team, jailbreak or adversarial testing | 0% | 0% | 0% | 0% | 1% | 2% | 4% | 1% | 16% | 1% | 0% | 0% | 7% | 0% | 14% | 0% | 0% | 3% | 0% | 0% | 15% | 7% | 0% | 0% | 5% | 5% | 0% | 0% |
| Do hands-on professional work (models, analyses, simulations) | 4% | 3% | 0% | 0% | 0% | 0% | 4% | 0% | 3% | 6% | 7% | 0% | 0% | 0% | 0% | 0% | 0% | 6% | 0% | 0% | 10% | 1% | 0% | 0% | 6% | 5% | 1% | 0% |
| Perform physical tasks for robot data | 0% | 0% | 2% | 0% | 0% | 0% | 0% | 0% | 0% | 1% | 0% | 0% | 0% | 0% | 0% | 2% | 0% | 17% | 0% | 0% | 0% | 0% | 0% | 3% | 0% | 0% | 1% | 0% |
Sample. 3,260 roles open on 17 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Handshake AI, Invisible, Mercor, micro1, Mindrift, OneForma, OpenTrain AI, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, RemoExperts, Remotasks, Sigma AI, Sovrano AI, SuperAnnotate (SME), Terac, TransPerfect DataForce, Turing, Vetto, Welo Data and xAI (SpaceXAI)), 88.9% of the 3,668 open roles; the boards that publish descriptions are expert networks, so these roles lean towards expert work. Each cell is the share of the platform's open roles read that mention the task (roles read in the column header).
A role mentions a task when its description contains one of the task's documented patterns, anywhere in the text: a mention is not necessarily the main task, and a role often mentions several.
Listings only: a share of a platform's open roles, not of its hires or projects. Platforms write descriptions to their own template, so a task one platform's template always names counts in every one of its roles.
Source. AITraining.jobs Research, What AI Trainers Do, live data.
Figure 5
How many different tasks a role describes
Do AI training roles describe one task or a mix?
| Distinct tasks mentioned | Roles | Share of roles read |
|---|---|---|
| No task named | 163 | 5.0% |
| 1 task | 789 | 24.2% |
| 2 tasks | 502 | 15.4% |
| 3 tasks | 394 | 12.1% |
| 4 tasks | 660 | 20.2% |
| 5 tasks | 357 | 11.0% |
| 6 or more tasks | 395 | 12.1% |
Sample. 3,260 roles open on 17 Oct 2026 whose job board publishes a full description (AfterQuery, Anyone AI, Appen, Babel Audio, Braintrust, Claru, Handshake AI, Invisible, Mercor, micro1, Mindrift, OneForma, OpenTrain AI, Outlier (Scale AI), Pasiflora AI, Perle Labs, Pila8, RemoExperts, Remotasks, Sigma AI, Sovrano AI, SuperAnnotate (SME), Terac, TransPerfect DataForce, Turing, Vetto, Welo Data and xAI (SpaceXAI)), 88.9% of the 3,668 open roles; the boards that publish descriptions are expert networks, so these roles lean towards expert work.
A role mentions a task when its description contains one of the task's documented patterns, anywhere in the text: a mention is not necessarily the main task, and a role often mentions several.
Out of the 25 tasks in the taxonomy. A role naming none describes its work in words no pattern reads (a project overview, a list of requirements only).
Source. AITraining.jobs Research, What AI Trainers Do, live data.
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The public job boards of the AI training platforms this site tracks, read every day. Full descriptions are read for the roles whose feed 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.
- Mention
- A description mentions a task when it contains one of the task's documented patterns (whole words, case-insensitive, never across two lines), anywhere in the text: the duties, the requirements or a note on the project. A mention is not necessarily the main task, and a role often mentions several.
- Task
- One of 25 activities a description can name, from writing prompts, ideal answers, rubrics and evaluation tasks, through rating, ranking, fact-checking and red-teaming model output, to coding, annotating, transcribing, translating, recording and physical tasks for robot data. Each has a published pattern, tested on real sentences.
- Not a task
- Hiring steps and company boilerplate are kept out: an application read against a rubric, an AI interview, 'no screen recording' or 'professionals, not annotators' do not count as writing rubrics, holding conversations, recording or annotating.
- Pay by task
- The median hourly rate advertised by the roles mentioning a task. A median needs 8 roles stating a rate, and is ranked only when they come from at least 2 platforms; a median resting on one platform is shown, marked, and not ranked.
- Coverage
- Only roles whose job board publishes a full description are read (Mercor, micro1, AfterQuery and Braintrust, about three in ten open roles); each figure states how many that is.
- Open role
- A role listed by a given day and still in its platform's feed that day.
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- Each role is classified from its title and description into one of the twelve kinds of AI training work this site tracks, from AI evaluation and coding to multilingual and audio work. Every kind links to its own page.
- Window
- Live: the last 28 complete days, in UTC. Edition: one calendar month, in UTC.
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.
- Descriptions are published by about three in ten open roles, all at expert networks: the figures describe those roles, lean towards expert and senior work, and say little about microtask crowds and the platforms that publish titles only.
- A mention is not the main task, and a requirement counts like a duty ('experience in translation' mentions translating). Platforms write to their own templates, so a task one template always names counts in every one of its roles.
- A pattern can miss a task phrased in an unusual way; nothing is inferred beyond what the text says. A pay difference between tasks is an association: tasks travel with kinds of work and seniority.
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.
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Citation
AITraining.jobs (2026). What AI Trainers Do (live data, 20 Sep 2026 to 17 Oct 2026). https://www.aitraining.team/research/what-ai-trainers-do (accessed 18 Oct 2026)
BibTeX
@misc{aitrainingjobs_what_ai_trainers_do_live,
author = {{AITraining.jobs}},
title = {What AI Trainers Do (live data, 20 Sep 2026 to 17 Oct 2026)},
year = {2026},
howpublished = {\url{https://www.aitraining.team/research/what-ai-trainers-do}},
note = {Accessed 18 Oct 2026},
}More research
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- AI Training Job TitlesWhat is AI training work called, and does the title say anything about the pay?Read the report
- Programming Languages in AI TrainingWhich programming languages are AI labs hiring coders to train models in, and what does each pay?Read the report
- The Expert Scarcity Index for AI TrainingWhich expertise and languages are hardest to recruit for AI training work right now?Read the report
- Real-World Data Collection WorkWho is hiring people to collect real-world data for robots and physical AI, where, and at what pay?Read the report
- The State of AI Training PayWhat does AI training work pay, by kind of work and by platform?Read the report