Data Annotator
Micro1 • Remote
Education
Master's
Type
Hourly
Pay Rate
$6–$10/hr
Actively Hiring
20 openings
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From the Micro1 listing
Role Title: Data Annotator Role Type: Contractor Location: Remote micro1 is engaging Data Annotators to contribute expertise to a client-driven project focused on high-quality data labeling. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work
- Precisely annotate video and audio samples according to detailed project guidelines and protocols.
- Review, validate, and enhance existing annotations to maximize data accuracy and consistency.
- Identify, flag, and document edge cases and ambiguous data points for further clarification.
- Collaborate with project coordinators to clarify annotation criteria and resolve uncertainties.
- Maintain meticulous records of completed annotations and submit deliverables within established milestones.
- Provide feedback on annotation tools and workflow for continuous process improvement.
- Ensure all annotated data meets quality assurance standards and project requirements. Preferred Qualifications
- Demonstrated experience in data annotation, especially with video and audio content.
- Exceptional attention to detail and a methodical approach to complex data tasks.
- Proficiency in both written and verbal English communication.
- Ability to interpret and execute highly specific annotation instructions.
- Experience working independently on remote projects with minimal supervision.
- Strong analytical skills, with the ability to make objective decisions about nuanced data.
- Familiarity with data labeling platforms or annotation tools (a plus).
Requirements
- Data annotation
- Attention to detail
- Must be eligible to work in Remote
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a AI Data Annotator role, written in-house to help you prepare.
How do you approach a labeling task when the guidelines don't clearly cover the example in front of you?
I make my best call based on the closest documented case and the guideline's underlying intent, then flag the example separately rather than letting it pass silently as if it were a clear-cut decision. Guessing quietly is how the same ambiguous case ends up labeled inconsistently across a dataset.
What's your process for staying consistent across a long labeling session, when fatigue can quietly shift your judgment?
I take short breaks between batches and spot-check a few earlier labels against my current judgment before continuing, since drift tends to happen gradually and I won't notice it in the moment without comparing back. I also try to label similar example types together rather than jumping between very different categories.
How do you decide when to flag an example as ambiguous versus making your best call and moving on?
I flag it if two reasonable people following the same guidelines could plausibly land on different labels, rather than just because the example is hard. Difficulty alone doesn't mean ambiguity, and flagging every hard case would bury the genuinely ambiguous ones that need guideline clarification.
How do you interpret conflicting instructions between an old guideline document and a newer update?
I treat the newer update as authoritative by default, but I check the date and scope of the update first, since sometimes an update only addresses a specific case and the old guideline still applies elsewhere. If it's genuinely unclear which one governs my current example, I flag it rather than assume.
Key responsibilities
- Precisely annotate video and audio samples according to detailed project guidelines and protocols.
- Review, validate, and enhance existing annotations to maximize data accuracy and consistency.
- Identify, flag, and document edge cases and ambiguous data points for further clarification.
- Collaborate with project coordinators to clarify annotation criteria and resolve uncertainties.
Why this role
The Data Annotator role at micro1 pays $6-$8 per hour for people who apply careful, consistent attention to detail across high-volume data annotation tasks. No prior AI experience is required, since the project is built around detailed annotation work rather than subject-matter expertise. This role suits someone comfortable with repetitive, precision-focused labeling.
Skills and categories
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Common questions
What does the Micro1 application process look like?
Expect a screening interview with Zara, Micro1's AI recruiter. Prepare for it like a real video call: good lighting, clear audio, verbal answers to technical questions. A human manager reviews the recording afterward, and some roles add a short skills assessment on top.
Can I apply to Micro1 from outside the US or UK?
Yes. Micro1 accepts applicants from most countries worldwide, unlike DataAnnotation or Outlier, both of which cap access to a handful of English-speaking countries. Most roles still require strong written and spoken English.
What does task-based AI training work look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does Generalist work look like for a Data Annotator ?
Tasks here are scoped to Generalist, not generic labeling. As a Data Annotator , expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Generalist) rather than following a one-size-fits-all rubric. If you don't have hands-on Generalist background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Data annotation, Attention to detail, English, and Entry Level are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
What does the 'openings' count on this listing mean?
It's Micro1's live count of how many candidates it's still trying to place for this specific role, 20 right now, not a countdown on your individual application. A higher number signals more active demand; it doesn't lower the bar for acceptance.
How much does this specific role pay?
This listing is posted at $6–$10/hr, an hourly rate. The range reflects experience level and negotiated terms, not a placeholder, so where you land in it depends on your background and the assessment. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.
What happens when I click Apply on this listing?
You'll be taken to Micro1's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Do I need a Master's to qualify?
This role lists a master's degree as a requirement. In practice, the domain assessment is the real gate. If you can pass it, the degree is usually secondary. However, some platforms verify credentials formally, so list your actual qualifications accurately on your profile.