Join OpenTrain to review and annotate AI text outputs at $50/hour, working 20+ hours/week as a part-time contractor. Apply complex guidelines, flag edge cases, and produce evaluation ratings and classifications that improve model training quality.
Generative AI & RLHF
Remote Hourly · $50/hr
$50/hr
Compensation
1 country
Eligibility
Intermediate
Experience
Jul 21, 2026
Posted
Open to applicants in
United States
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OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people discover projects, build a unified AI-training portfolio, and grow sustainable freelance careers in the human side of AI.
OpenTrain is hiring this role directly: when you work here you join a distributed team focused on rigorous, high-quality human review that makes modern AI systems safer and more reliable.
About AI Training Work
AI training (data labeling / annotation / human feedback) is the human work behind how models learn. Tasks include evaluating model outputs, rating responses, and flagging errors so downstream training improves.
This field is fast-growing and well-suited to flexible, part-time work. Many contributors work remotely, follow structured guidelines, and build growing portfolios of annotation experience.
Work that directly shapes how AI systems behave
Usually flexible and accessible work that rewards attention to detail
Great entry point for people with QA, trust & safety, or reviewer backgrounds
The Role
We are recruiting an AI Output Reviewer to evaluate and annotate text outputs used in advanced AI training pipelines. This is precision-heavy review across high-volume batches where consistency and accuracy matter.
This is a part-time contractor role requiring 20+ hours per week. Pay is $50 USD per hour. Candidates must be located in the United States and fluent in English.
Employment type: Contractor, Part-time
Time requirement: 20+ hours/week
Location: United States (remote/distributed)
Pay: $50/hour (PAY_PER_HOUR)
What You'll Do
You will review AI-generated text, apply detailed guidelines, and produce structured feedback and labels that downstream trainers and models use. The work focuses on spotting subtle errors, inconsistencies, and ambiguous cases.
Review AI outputs with extreme attention to detail
Evaluate and annotate responses using complex guidelines
Assign evaluation ratings and classification labels to text
Identify subtle errors, inconsistencies, and edge cases
Provide clear, structured written feedback that improves training
Flag unclear instructions and ambiguous examples proactively
Requirements
You must have prior experience performing review, rating, or annotation work in human data or AI training pipelines, and be comfortable following nuanced guidelines precisely. Strong written reasoning and sustained focus during repetitive batches are essential.
Prior experience as a reviewer, rater, or contributor in AI/data pipelines
Comfort applying complex guidelines consistently and without deviation
Strong written communication and clear reasoning for feedback
High reliability, consistency, and accuracy across long task batches
This role is a great fit for people with hands-on experience in human review workflows who enjoy detail-focused, impact-driven work. If you have experience in QA, content moderation, trust & safety, or as a search/rating rater, you’ll find your skills transfer well.
We welcome intermediate-level candidates who can demonstrate past review work and a dependable approach to following rules and producing clear written rationale.
Intermediate-level experience in annotation or structured review
You prefer batch work with tight accuracy standards
You can commit to 20+ hours per week as a contractor
How It Works
Apply through OpenTrain (creating an account is free). If selected, you'll receive access to task batches, detailed guidelines, and the annotation interface. Work is paid hourly at the stated rate and managed on a contractor basis.
The work centers on text data and uses evaluation-rating and classification label types. Expect repetitive, guideline-driven workflows where accuracy and clear feedback are the main performance signals.
Data type: Text
Label types: Evaluation Rating, Classification
Onboarding includes guideline training and quality checks
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