ClaruData annotation
Gameplay Annotation Specialist
up to $25/hr
About this role, in Claru's words
Your job is to generate high-quality human demonstration data by playing games and simulations under controlled conditions. You will follow session protocols that specify the game, the scenario, the objectives, and the annotation requirements. After each session, you fill out a structured form documenting your strategies, mistakes, and key turning points. This data is used to train and evaluate game-playing AI agents.
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Claru's words
Posted by Claru, reproduced here so you can judge the role before clicking. Original posting ↗
Your job is to generate high-quality human demonstration data by playing games and simulations under controlled conditions. You will follow session protocols that specify the game, the scenario, the objectives, and the annotation requirements. After each session, you fill out a structured form documenting your strategies, mistakes, and key turning points. This data is used to train and evaluate game-playing AI agents.
We are looking for people who can play systematically and document their reasoning. Gaming experience is important, but so is the ability to follow protocols and produce clean annotation logs. If you have done game QA, speedrunning, or competitive gaming, those backgrounds translate well.
Sessions run 2-4 hours and are scheduled in advance. Most contributors complete 3-4 sessions per week. You will need a PC that meets minimum specs for the game engines we use (we will provide these during onboarding). A stable internet connection is required for real-time data upload.
Location: Remote (US)
Working with ClaruPay, getting started and work, from Claru's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Set by each project. Its US capture posting pays by ACH every two weeks, and its Latin America and Asia postings pay by Wise, Payoneer or a local equivalent. claru.ai/for-annotators, claru.ai/jobs/household-capture-us, claru.ai/jobs/household-capture-latam, claru.ai/jobs/household-capture-asia
- Before your first paid task
- Create a profile. If you are matched, you see the task, the requirements, the acceptance criteria and the pay before you decide. claru.ai/for-annotators
- How much work
- A profile does not guarantee a match, a start date, an amount of work or payment. claru.ai/for-annotators
- Contract
- Contractor, under terms with Reka AI, Inc., doing business as Claru AI. claru.ai/jobs/household-capture-latam, claru.ai/terms
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Data annotation roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Claru's posting. How we count.
Pay across the field: Data annotation
Across 58 roles in this field with a stated hourly rate in US dollars, on 10 platforms, the middle half pays $15 to $50 an hour at the top of the range, and the median is $28. This role's top rate, $25, is in the middle half. Of the 30 distinct rates we count, 14 are lower and 15 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Claru (this platform) | 26 | $10 to $100 · median $35 |
| micro1 | 14 | $10 to $80 · median $15 |
| Alignerr | 7 | $24 to $120 |
| Grayder | 3 | $45 to $100 |
| Mercor | 2 | $50 to $65 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 13 Sep 2026, and still on Claru's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Claru
- First seen by AIPayList
- Last seen live
- Listing ID
- gameplay-annotation-specialist
Pay as the source states it: “$20–25/hr”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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