Gameplay Data Capture Specialist

$10–15/hrrate as listed

Record structured gameplay sessions — screen capture, input logs, and timestamped annotations — that become training data for AI agents learning to play and reason about games. Work is remote, task-based, and paid hourly in the $10–15 range as observed on micro1; volume depends on active data collection campaigns.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work involves

Gameplay data capture sits at the unglamorous, essential end of AI training: someone has to play the game correctly, on spec, while the recording tools run. A typical task packet gives you a title, a platform, a capture configuration (resolution, frame rate, input logging, audio on or off), and an objective — clear a level a specific way, trigger a particular enemy behavior, demonstrate a UI flow, or produce N minutes of clean exploration footage without deaths or menu detours.

Day to day you will:

Set up and verify capture tooling (OBS or a proprietary client, input loggers, sometimes emulator save-states) before each session
Play to the brief rather than to win — repetition, deliberate mistakes, and boring footage are often the point
Annotate segments with timestamps and event labels: state transitions, objective completion, failure causes, ambiguous frames
Run QC on your own output — dropped frames, desync between video and input logs, overlays or notifications leaking into frame, audio bleed
File clean handoffs with metadata that matches the schema exactly, since malformed metadata usually means the session is discarded

What the platform screens for

micro1's screening is AI-led and conversational. Expect it to probe whether you actually own the hardware and games you claim, whether you can describe a capture pipeline in specifics (codec, container, frame rate, where desync comes from), and whether you understand that a beautiful playthrough can be a useless data sample. Follow-ups get concrete fast: if you say you've used OBS, expect questions about scene setup and encoder settings. Reliability and honest availability matter as much as skill here — repeatable, on-spec output beats virtuosity.

Logistics

Fully remote and largely asynchronous, with task packets claimed from a queue and turned around on stated deadlines. Sessions are hardware-dependent, so a stable machine, decent upload bandwidth, and the ability to record without background processes interfering are non-negotiable. Hours are flexible but campaign-driven: some weeks offer 20+ hours, others little, and pay in the $10–15/hr band reflects observed rates rather than a guarantee.

What they look for

gameplay

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you have a Windows PC, Mac, or Linux machine with at least 8GB of RAM that you can dedicate to gameplay capture tasks?
Own a PC or Mac capable of running OBS or a proprietary capture client · required
Can you reliably achieve at least 3 Mbps upload speed from your location, tested within the last 30 days?
Access to a stable upload connection (≥3 Mbps) · required
Do you own or have a valid account for the primary gaming platforms you'll be capturing on (e.g., Steam, console accounts, emulator ROMs you own)?
Own or have legal access to the games and platforms you'll capture on · required
Have you previously used OBS, Bandicam, Camtasia, a proprietary game capture tool, or similar software to record a video file of at least 5 minutes?
Hands-on experience with capture software · preferred
Are you able to claim task packets from a queue, work independently, and submit completed sessions by stated deadlines without daily check-ins or synchronous meetings?
Ability to work asynchronously on deadlines · preferred

0 of 5 answered

Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Whether you've actually used capture software hands-on and understand the relationship between codec, container, and output quality, not just watched a tutorial.
A strong answer: Name the specific encoder (H.264, NVENC, etc.), frame rate, and bitrate you selected, and explain why that choice matched your hardware or your output target—e.g., 1080p60 at 8Mbps for file size, or lower bitrate for stable upload.
Where people lose it: Saying you 'used OBS' without being able to name an encoder or explain why you chose your bitrate; talking about resolution and frame rate but not the codec or container format that ties them together.