Red Team Safety Classifier Evaluation AI Trainer, $55–$65/hour
Project Overview: Join a growing community of professionals advancing the next wave of AI. As an AI Trainer, you’ll play a hands-on role by analyzing and providing feedback on data to improve LLM performance, helping ensure that the next generation of AI technology is accurate and trustworthy. We are seeking a skilled AI Safety Evaluator / Red Team Prompt Engineer to work as a project consultant in our AI Labor Marketplace. This is not a full-time employment position — you will be engaged as an expert project consultant on a contract basis. Location: U.S.-based experts only Engagement: Part-time, project-based expert evaluation work Work Type: Remote Project Summary: A fast-paced AI safety evaluation sprint focused on adversarial prompt generation and safety classification. Contributors will create and assess high-difficulty, edge-case scenarios, applying structured labeling, severity scoring, and policy-based reasoning to improve model safety performance. Consultant Engagement Terms: This is a project-based consultant role. Consultants will be paid on a per-project basis; hourly rates are estimates based on anticipated completion time. Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers (subject to those vendors’ allowances). Responsibilities: Contributors will:
- Design adversarial prompts that expose edge cases in AI safety systems
- Apply structured safety classifications, including category and severity
- Write concise, policy-grounded rationales for decisions
- Review and validate peer submissions for accuracy and quality
- Identify ambiguous or difficult-to-classify scenarios
- Maintain consistency across high-volume evaluation tasks
Expected Outcomes:
- High-quality adversarial examples suitable for model evaluation
- Accurate and consistent safety labels and severity ratings
- Clear, defensible rationales aligned with policy guidelines
- Reliable QA feedback improving dataset quality
Qualifications:
- Experience in AI safety, LLM evaluation, red teaming, or trust & safety
- Strong prompt engineering and analytical reasoning skills
- Familiarity with safety taxonomies and policy-based classification
- Ability to work independently and maintain high-quality output
- Prior experience with annotation or evaluation platforms preferred
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