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Requirements and responsibilities
micro1 is engaging Mathematics Professors and Researchers with a PhD in mathematics to participate in a dynamic project for a customer. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This is an opportunity for experienced academics and research professionals to impact the future of AI by sharing their mathematical insight and problem-solving abilities.Scope of WorkReview, analyze, and evaluate complex mathematical content to generate detailed feedback and domain-specific insights for AI model training.Develop and contribute original mathematical problems, proofs, and teaching materials across a range of undergraduate and graduate topics.Annotate, critique, and refine mathematical datasets for accuracy, depth, and pedagogical value.Collaborate with other subject matter experts and project stakeholders to define quality standards and subject coverage.Draft and edit clear written explanations, solutions, and instructional content tailored for AI learning and reasoning tasks.Participate in iterative review cycles to enhance the robustness and diversity of mathematical data.Preferred QualificationsPhD in Mathematics or a closely related quantitative field.Demonstrated experience in university-level teaching or advanced mathematical research.Proven ability to communicate intricate mathematical concepts with precision and clarity, both in writing and verbally.Strong analytical skills and attention to detail in reviewing mathematical work and educational content.Familiarity with contemporary mathematical literature and ongoing research trends.Experience developing learning materials or problem sets for mathematics education is a plus.Intellectual curiosity about artificial intelligence and its implications for mathematical discovery and instruction.
Optionally, you can add more information later (benefits, pre-screening questions, etc.)