Mathematics QA Lead - Remote
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About the Role
Job Title: Mathematics Quality Assurance Lead Job Type: Contract Location: Remote About This Role In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead to oversee quality, consistency, and trainer performance across mathematics AI training projects.
Key Skills for This Role
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About This Role
- In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead to oversee quality, consistency, and trainer performance across mathematics AI training projects.
- You will review AI-generated math content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.
- You will assess work for mathematical accuracy, logical reasoning, calculation correctness, proof validity, notation quality, clarity, formatting, instruction-following, and adherence to project-specific rubrics.
- You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
- This role requires strong mathematics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams.
- This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs.
- Your mathematics quality leadership will directly help improve the world’s premier AI models by ensuring that math training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations.
- Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise.
- This will also provide you with access to future projects available through our expert network.
- Your profile
- Bachelor’s, Master’s, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or a closely related quantitative field.
- Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear mathematical feedback in English.
- 3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math-content review.
- Strong understanding of core mathematics topics such as algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs.
- Ability to evaluate math content against detailed rubrics and identify issues such as incorrect assumptions, flawed reasoning, invalid proofs, calculation errors, notation problems, missing steps, hallucinated facts, or incomplete explanations.
- Comfortable reviewing both conceptual explanations and step-by-step solutions, including whether each step logically follows from the previous one.
- Familiarity with mathematical tools or workflows such as LaTeX, Python, MATLAB, R, WolframAlpha/Mathematica, GeoGebra, Desmos, spreadsheet modeling, or symbolic computation tools is preferred.
- Experience leading or supporting remote teams of trainers, annotators, reviewers, educators, technical writers, or QAs is strongly preferred.
- Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
- Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
- Experience with AI training, data annotation, large language models, prompt/response evaluation, mathematical content QA, or rubric-based LLM evaluation is a strong plus.
Key Responsibilities
- Quality monitoring: Spot-check mathematics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
- Mathematical review: Evaluate AI-generated math explanations, proofs, derivations, calculations, word-problem solutions, diagrams/descriptions, and step-by-step reasoning for correctness and clarity.
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and math-specific review standards.
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around reasoning validity, notation, assumptions, solution methods, proof structure, formatting, and rubric interpretation.
- Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
- Documentation: Create and maintain mathematics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
- Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mathematics-specific review requirements.
- Quality alignment: Ensure all trainers and QAs apply mathematics guidelines consistently and understand updates as projects evolve.
- Error-pattern analysis: Identify recurring issues such as skipped reasoning steps, invalid simplifications, wrong formulas, notation inconsistencies, arithmetic mistakes, or answers that are correct but poorly justified.
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mathematics AI training projects.
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