Math Experts for LLM Annotation

I’m assembling a small, highly-skilled team of mathematics domain experts to help me refine a large-language model. Your main responsibility will be data annotation: taking raw mathematical questions, proofs, theorems, solution outlines, and related explanatory text and tagging them with the precise metadata the model needs (topic, sub-topic, difficulty level, prerequisite concepts, step-by-step reasoning, common misconceptions, etc.). Because this work directly feeds the model’s training loop and later evaluation, accuracy matters more than speed. You should feel comfortable distinguishing between, say, elementary number theory and analytic number theory, or spotting a subtle gap in a proof that could mislead the model. Familiarity with JSON-based annotation formats, Python notebooks, or any established annotation platform is a plus; if you prefer another tool, let me know and we can adapt. Deliverables (per milestone) • A curated batch of fully annotated mathematical items, validated for completeness and consistency • A brief log explaining any edge cases, ambiguous phrasing, or assumptions you encountered Demonstrated expertise in Algebraic Geometry I’ll review the first small batch together with you so we can lock in conventions; after that you’ll work more autonomously, with periodic check-ins to ensure labeling guidelines stay rock-solid. If you love getting the details of mathematics right and want to see that precision drive a smarter AI, I’d love to collaborate.

Project ID: 40685855