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Why this grade This listing scored 70/100, which is a B. It lost the most ground on freshness. See the breakdown
- Pay transparency 25 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 10 / 10 Whether more than one source carries this listing.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Operations Entry level Contractor
Role Title: Data Entry Keyer
Role Type: Contractor
Location: Remote
micro1 is engaging Data Entry Keyers to contribute to a customer's advanced AI benchmark project. 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
- Design and produce expert-level evaluation tasks that simulate real-world data entry and validation challenges for AI agents.
- Construct and curate large, complex datasets—including CSVs, PDFs, spreadsheets, and technical documents filled with realistic errors such as malformed records, missing data, and inconsistent formats.
- Define the correct final state for each task, specifying the exact error cases and reconciliation requirements that an AI must address.
- Author detailed grading rubrics (35+ criteria) for assessment of AI agent outputs, focusing on both accuracy and completeness in error detection.
- Ensure all authored tasks mirror the authentic complexity and standards of highly regulated or audit-sensitive environments.
- Collaborate asynchronously through precise written and verbal communication to iterate and refine evaluation materials.
Preferred Qualifications
- Extensive experience in data entry, quality assurance, or data validation within regulated or audit-sensitive domains such as healthcare claims, finance back office, or legal operations.
- Demonstrated ability to achieve and document high accuracy standards, including measurable error rates and outcomes.
- Strong skills in detecting and analyzing data inconsistencies, silent truncations, and formatting irregularities across diverse file types.
- Proficient written English, enabling clear drafting of complex evaluation tasks and comprehensive grading rubrics.
- Exceptional attention to detail and a disciplined, process-oriented work style.
- Experience contributing to projects with high stakes for compliance, accuracy, or data integrity is highly valued.
- Comfort working independently and communicating proactively within remote, distributed project environments.
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 13 Aug 2026 Himalayas first sighting
Seen on 1 board over 35 days.