Role Title: STEM / Quant Bachelor

Role Type: Contractor

Location: Remote

micro1 is engaging STEM / Quant Bachelors to contribute their expertise on a leading-edge customer project. 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 a unique opportunity to leverage your STEM, finance, or quantitative background in a highly impactful context, annotating and reviewing educational content across math, physics, chemistry, finance, and economics. Clear, thoughtful written and verbal communication is central to this engagement, as project success depends on both the accuracy and clarity of your insights.

Scope of Work

1. Analyze and annotate a range of school-level and introductory college math, physics, chemistry, finance, and economics homework problems.
2. Review, edit, and provide feedback on annotated materials to ensure consistency and accuracy.
3. Collaborate via written and verbal discussions in long multi-turn chat sessions, providing thorough, well-reasoned responses.
4. Compare and assess two long-form responses side by side, evaluating clarity, correctness, and pedagogical value.
5. Document reasoning and highlight common misconceptions or errors in learning materials.
6. Contribute domain expertise to help refine AI model understanding in quantitative subjects.

Preferred Qualifications

1. Bachelor’s degree in math, science, engineering, economics, finance, or related field, or equivalent experience.
2. Solid grounding in quantitative analysis and problem-solving.
3. Proficiency in Python and familiarity with finance & economics concepts.
4. Native or near-native command of written English with emphasis on clarity and precision.
5. Demonstrated ability in careful reading and analysis of complex, multi-turn conversations.
6. Experience with annotation, educational content review, or similar work involving detailed feedback is strongly preferred.
7. Comfortable collaborating remotely with diverse teams and adapting feedback into actionable improvements.