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As AI models increasingly generate professional-grade B2B distribution strategies, inventory management workflows, and wholesale pricing models, 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 wholesale trade, B2B distribution, and bulk purchasing agreements. 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 wholesale and logistics-related tasks. Quality Assurance & Fact-Checking: Ensuring all generated tasks and scoring criteria reflect strict, real-world B2B market standards, inventory compliance, and supply chain realities. 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 wholesale trade, B2B sales, procurement, or distribution management sectors, with a deep understanding of industry standards, wholesale terminology, and supply chain logistics. 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