Data Annotator

$6–8/hrrate as listed

Label and quality-check audio and video samples against detailed project guidelines for AI training datasets. Contract, fully remote, with observed pay in the $6–8/hr range and volume that varies by customer project.

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

The work

This is hands-on annotation, not model critique. You'll work through queues of audio and video samples — applying labels, marking timestamps or segments, transcribing or verifying spoken content, and flagging samples that don't fit the taxonomy. A second stream of work is review: checking annotations others have already produced, resolving disagreements, and correcting inconsistencies before batches ship.

Guidelines change. A meaningful part of the job is reading updated instruction documents carefully, understanding why a rule changed, and re-applying it consistently across old and new work. You're also expected to document your reasoning on ambiguous cases so a project lead can audit the decision later, and to surface edge cases the guidelines don't cover instead of guessing silently.

What the screen looks for

Guideline literalism under pressure — can you follow a rule as written even when your instinct disagrees, and raise the disagreement through the right channel?
Consistency across volume. Screens often present near-identical samples to see whether you label them the same way.
English comprehension for audio — accents, overlapping speech, poor recording quality.
Honest ambiguity handling. Flagging a genuinely unclear sample scores better than a confident wrong label.
Prior exposure to labeling tools (CVAT, Label Studio, Audacity, or platform-native tools) helps but isn't required.

Logistics

Contractor engagement, fully remote, async. Work is pulled from queues rather than scheduled, so hours are flexible, but projects run in bursts — heavy weeks followed by gaps. Pay in the $6–8/hr band has been observed for this listing; micro1 sets rates by project and region, and neither the rate nor ongoing volume is guaranteed. Expect a stable internet connection, quality headphones for audio tasks, and a desktop or laptop as baseline requirements.

What they look for

Data Annotation
Attention to detail

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.

Are you able to read and understand detailed written project guidelines in English and to write clear annotations and documentation in English?
English proficiency · required
Are you able to work from home on a flexible schedule and have reliable internet and a device (computer, tablet, or phone) to complete annotation tasks?
Remote work capability · required
Have you previously annotated, labeled, or transcribed audio or video content in a professional or structured project?
Audio and video annotation experience · preferred

0 of 3 answered

Included with this listing

Interview prep — 10 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 the candidate has hands-on annotation experience and can articulate the actual decision-making process, not just claim familiarity with labeling.
A strong answer: A concrete narrative naming the content type (transcripts, sentiment, objects, events, safety flags), the exact criteria applied, and a concrete instance of interpreting an ambiguous sample or borderline case—showing judgment, not just compliance.
Where people lose it: Vague reference to 'working with data' or 'being detail-oriented' without a real project or specific annotation task; inability to name what was labeled or how decisions were made.