What You Will Do:
Evaluate AI-generated content in French 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 French 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.
Originally posted on Himalayas
