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High Risk AI Behavior Trainer, $30-45/hour

LinkedIn
3 hours ago
Contract
Remote
United States
$30 - $45 USD hourly
Trainer

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 Trust & Safety / AI Evaluation professional 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:

Contributors will design realistic prompts and multi-turn conversational scenarios to evaluate behavioral risks in large language models, along with structured annotations. Work focuses on nuanced, policy-relevant edge cases across high-risk categories such as social profiling, crisis handling, and human-AI interaction risks.


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:

  • Create high-quality single-turn prompts and multi-turn scenarios for AI evaluation
  • Design realistic, policy-relevant edge cases reflecting real-world user behavior
  • Apply structured annotations accurately and consistently
  • Interpret and follow evolving safety and evaluation guidelines
  • Review peer submissions for quality and policy alignment (for qualified contributors)
  • Provide concise feedback on flagged or low-quality tasks


Expected Outcomes:

  • Consistent production of high-quality, realistic prompts and scenarios
  • Accurate and reliable annotations aligned with project taxonomy
  • Identification and surfacing of meaningful edge cases in AI behavior
  • Maintained throughput and quality standards over time


Qualifications:

  • 1–3+ years of experience in trust & safety, AI evaluation, content moderation, prompt engineering, or related fields
  • Strong writing and scenario design skills
  • Demonstrated ability to apply judgment in ambiguous or policy-sensitive contexts
  • Experience with annotation or structured evaluation workflows preferred
  • Familiarity with AI systems, LLMs, or human-AI interaction patterns is a plus