Revit Family Development Engineer
Listed on 2026-07-27
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Business
AI Evaluation, AI Business & Operations
Math Expert (PhD)
Role Type: Contractor
Location: Remote
micro1 is a leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms real‑world expertise into high‑quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.
We are engaging Math Experts (PhD) to contribute to an advanced AI training project for a customer. In this role, you will 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.
Scope of Work- Develop and provide comprehensive, accurate, and insightful responses to complex mathematics prompts spanning undergraduate and graduate curricula.
- Review, refine, and deliver “golden responses”—high‑quality model answers that exemplify subject mastery for use in AI training.
- Collaborate with a distributed team of experts to ensure clarity, precision, and educational value in all mathematics content produced.
- Analyze and interpret intricate mathematical problems, proofs, and concepts, distilling them into structured and accessible explanations.
- Contribute feedback to improve project guidelines, response standards, and content workflows as the engagement evolves.
- Adhere to project requirements regarding format, quality, and timeliness of deliverables.
- PhD in Mathematics or a closely related discipline from an accredited institution.
- Proven track record of academic excellence and subject‑matter expertise, especially at the graduate level.
- Exceptional written and verbal communication skills; ability to articulate complex concepts clearly and succinctly.
- Experience authoring or reviewing mathematics materials, such as textbooks, exams, problem sets, or journal articles.
- Familiarity with various branches of pure and applied mathematics.
- Demonstrated attention to detail and commitment to producing precise, high‑quality work.
- Adaptability and openness to collaborative, iterative feedback in a remote expert network environment.
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