Freelance AI Evaluation Scenario Writer
Mindrift • India • Posted 53 days ago
Education
Any
Type
Pay Rate
$12/task
Posted
53d ago
Role Overview
Help bridge the gap between human creativity and Foundation Models. In this role, you will evaluate AI outputs for distinctiveness, tone, and stylistic nuance. Work may involve "Creative RLHF," where you rank different creative writing drafts, or "Factuality Verification," ensuring the model can be creative without hallucinating facts.
Requirements
- Must be eligible to work in India
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
Compensation Analysis
Join the workforce powering the AI revolution. With a competitive rate of $12/hr and remote flexibility, this role allows you to balance professional growth with personal freedom. No previous AI experience is usually required—just your domain expertise.
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View All Mindrift Jobs →Frequently Asked Questions
How do I get started?
Review the hiring process above and follow the steps outlined. Each platform has different requirements, so make sure you meet the eligibility criteria before applying.
Is this work legitimate?
Yes. All platforms listed on aitrainer.work are legitimate and pay reliably. However, always verify payment methods and read reviews before committing significant time.
What equipment do I need?
For voice or audio roles at this pay level, you typically need a professional home studio setup (XLR microphone, treated room). Phone recordings or laptop mics are usually rejected by quality control.
How is my work used?
You are providing high-quality "ground truth" data. For writers, this means creative generation. For voice actors, it often means training Text-to-Speech models. Be sure to check the specific contract details regarding rights usage for your voice or likeness.
Is creative freedom allowed?
Yes and no. While you are hired for your talent, you must often follow strict style guides (e.g., "Speak in a neutral tone" or "Write in the style of a technical manual"). The goal is consistency for the dataset.