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