Data Entry AI Evaluation Task Designer

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping contributors discover projects, build a professional profile, and apply in minutes.

Creating an OpenTrain account is free, and your work can become part of a lasting portfolio as you grow in the AI-training industry.

About AI Training Work

AI training is the human side of building artificial intelligence. People create examples, evaluate model outputs, and establish quality standards that help AI systems become more accurate, reliable, and useful.

In this role, you will apply data-entry and validation expertise to design evaluation materials for AI agents. Your work will help assess whether these systems can identify errors, preserve information, and produce accurate final records.

The Role

OpenTrain AI is seeking a Data Entry AI Evaluation Task Designer to create realistic benchmark tasks that assess AI agents on data-entry and validation challenges. You will translate high-stakes accuracy and data-integrity practices into evaluation materials that reflect regulated or audit-sensitive environments.

This is a worldwide, fully remote contractor opportunity conducted in English. The role is part-time and requires at least 20 hours per week, with compensation ranging from $20 to $35 per hour.

  • Employment type: Contractor and part-time
  • Work arrangement: Remote, worldwide
  • Time requirement: 20 or more hours per week
  • Language: Proficient written English
  • Pay: $20–$35 per hour

What You'll Do

You will design and produce expert-level evaluation tasks that simulate real-world data-entry and validation challenges. Your materials should use realistic records, documents, and file-based workflows to test both accuracy and completeness.

You will also communicate precisely in writing and verbally while refining evaluation materials in an asynchronous, distributed work environment.

  • Construct and curate complex datasets using CSVs, PDFs, spreadsheets, and technical documents.
  • Introduce realistic malformed records, missing data, inconsistent formats, silent truncations, and other validation issues.
  • Define the correct final state, error cases, and reconciliation requirements for each task.
  • Author detailed grading rubrics with 35 or more criteria for evaluating AI-agent outputs.
  • Document measurable accuracy standards and expected outcomes.
  • Review diverse file types for inconsistencies and formatting irregularities.

Requirements

Experience in data entry, quality assurance, or data validation across diverse file types is valuable. You should be able to analyze inconsistencies, recognize formatting irregularities, and turn accuracy expectations into measurable evaluation standards.

Exceptional attention to detail, a disciplined process-oriented work style, and the ability to work independently are important for this distributed role. Prior AI experience is not required when you bring strong knowledge of data entry, quality assurance, or data validation.

  • Experience with data entry, quality assurance, or data validation.
  • Ability to identify malformed records, missing information, silent truncations, and formatting inconsistencies.
  • Skill in documenting accuracy outcomes and expected final states.
  • Ability to write complex evaluation tasks and comprehensive grading rubrics in proficient English.
  • Comfort working independently in an asynchronous remote environment.
  • Strong attention to detail and a consistent, process-oriented approach.

Helpful Background

Experience in healthcare claims, finance back-office operations, legal operations, compliance-sensitive work, or other environments where data accuracy and integrity are critical can help you create realistic evaluation standards.

Familiarity with reconciling records and documenting expected outcomes is also useful. The role is suited to professionals who understand how seemingly minor data issues can affect the reliability of a final record.

  • Healthcare claims experience
  • Finance back-office operations
  • Legal operations
  • Compliance-sensitive work
  • Record reconciliation and outcome documentation

Why Build Your AI Training Career With OpenTrain

AI training and data labeling are among the fastest-growing ways to work in technology. Contributors help shape how modern AI systems behave by preparing examples, reviewing outputs, and defining the standards models must meet.

OpenTrain helps you build a career in this field by bringing opportunities together in one place, helping you present your experience through a professional profile, and making it easier to grow a durable AI-training portfolio.

  • Work remotely from anywhere in the world.
  • Choose flexible part-time work that fits around your schedule.
  • Apply data-entry and quality-assurance expertise to cutting-edge AI development.
  • Build documented experience in AI evaluation and data labeling.
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