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e2finc

AI Quality Control Specialist - Japanese Language

Company

e2finc

Role

AI Quality Control Specialist - Japanese Language

Location

Independent Contractor

Job type

-

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Salary

Not disclosed by employer

Job description

About the Role

TrustScale is building scalable, high-quality human-in-the-loop systems to power AI. We are looking for an AI Quality Control Specialist - Japanese Language Specialist who can analyze, validate, and challenge AI-generated outputs with precision and consistency. This is not a proofreading role. You will act as a quality gatekeeper, ensuring outputs meet standards for accuracy, utility, and linguistic quality across large-scale workflows.

What You Will Do

  • Evaluate AI-generated content in Japanese across multiple task types (annotation, review, validation).
  • Apply structured quality frameworks to assess:
  • Accuracy and factual correctness.
  • Utility (alignment with user intent).
  • Language quality (fluency, tone, clarity).
  • Train vendors
  • Participate Clients Calls

Identify and flag

  • Hallucinations and misinformation.
  • Logical inconsistencies.
  • Cultural or linguistic mismatches.
  • Provide clear, structured feedback to improve upstream quality.
  • Detect patterns of errors across batches and contribute to quality insights.
  • Support calibration efforts to ensure consistent scoring across teams.
  • Contribute to guideline refinement and evaluation standards.

Who You Are

  • Professional proficiency in Japanese and strong command of English are required.
  • Highly analytical with strong critical thinking skills.
  • Comfortable working with ambiguous and evolving guidelines.
  • Detail-oriented with the ability to maintain consistency at scale.
  • Clear communicator, able to justify decisions and provide actionable feedback.
  • Naturally skeptical—able to question outputs and validate information.

Preferred Background

  • Journalism, editorial, or investigative research.
  • Linguistics, translation, or localization QA.
  • Content moderation / Trust & Safety.
  • Experience in AI data annotation, evaluation, or QA.

What Success Looks Like

  • High consistency in quality scoring across tasks.
  • Strong alignment with QA benchmarks.
  • Ability to detect non-obvious quality issues.
  • Feedback that improves annotator performance and overall output quality.
  • Contribution to a scalable, predictable quality system.

Why TrustScale

At TrustScale, we operate AI talent as a supply chain—structured, measurable, and optimized. You will be part of a system where quality is not subjective, but defined, measured, and continuously improved.

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