Information Specialist - Freelance AI Trainer Project

Project Overview We are sourcing independent Information Specialists to provide their expertise for an AI benchmark evaluation project. As AI models increasingly generate professional-grade data management strategies, information retrieval systems, and content architecture deliverables, their accuracy relies entirely on robust, expert-crafted training data. The objective of this project is to autonomously produce high-quality evaluation tasks, strong prompts, and clear, well-structured rubrics that generate clean, reliable data for model training.

Project Deliverables Scope Operate autonomously to design complex evaluation frameworks and provide structured training data. Expected deliverables include: Task Prompt Creation: Generating realistic, high-quality prompts that compel the AI model to produce complex, professional-grade deliverables specific to information science, data management, and knowledge organization. Rubric Development: Writing clear, well-structured evaluation rubrics with criteria that are highly specific, non-ambiguous, and easy to score.

Benchmark Evaluation Data Generation: Producing clean, reliable training data that directly aids in the evaluation and refinement of AI models handling complex information architecture and retrieval tasks. Quality Assurance Fact-Checking: Ensuring all generated tasks and scoring criteria reflect strict, real-world data governance standards, research methodologies, and information management best practices. Required Expertise To successfully fulfill the deliverables of this project, Contractors must possess deep industry knowledge to craft realistic professional scenarios.

Core skillset includes: Demonstrable professional expertise within the information science, library science, data governance, or knowledge management sectors, with a deep understanding of industry standards, metadata schemas, and search methodologies. Strong writing and prompt generation skills, with the ability to design highly realistic, complex information retrieval task scenarios for AI evaluation. Proficiency in rubric generation, specifically the ability to create objective, non-ambiguous scoring criteria that leave no room for subjective interpretation.

A meticulous, detail-oriented approach to fact-checking data architectures, search mechanics, and knowledge bases to generate reliable data for system benchmarking. We offer a pay range of $10-to-$30 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above.

Benefits

such as health insurance and PTO do not apply.