Mathematics QA Lead for AI Training Data Projects Remote
Overview
Remote contract role overseeing mathematics content for AI training data projects. You will review AI-generated math explanations and proofs, assess them against project rubrics, and deliver precise feedback to trainers and QAs. Maintain documentation, style guides, calibration tasks, and onboarding materials while coordinating with distributed teams to uphold consistent quality. Strong LaTeX-driven notation, Python-assisted calculations, and meticulous attention to detail are essential.
What You'll Do9
- 1Spot-check mathematics items to identify quality gaps and provide targeted feedback via direct messages, escalating critical issues when needed.
- 2Evaluate AI-generated explanations, proofs, derivations, and step-by-step solutions for accuracy and clarity.
- 3Keep trainers and QAs aligned by posting updates on Discord about new guidelines, workflow changes, and quality standards.
- 4Answer questions from trainers and QAs about reasoning validity, notation, assumptions, solution methods, and rubric interpretation.
- 5Manage activation of contributors by direct messaging inactive teammates, tracking follow-ups, and flagging availability issues.
- 6Create and maintain mathematics project documentation including style guides, trackers, FAQs, calibration tasks, and onboarding materials.
- 7Lead onboarding and training calls to set expectations and explain rubrics and review requirements.
- 8Ensure consistent application of mathematics guidelines as projects evolve across teams.
- 9Identify recurring error patterns and propose scalable QA process improvements for AI training work.
Requirements12
- 1bachelor's, master's, or phd in mathematics, applied mathematics, statistics, physics, engineering, computer science, mathematics education, or closely related quantitative field
- 2strong english language skills to follow guidelines and provide clear mathematical feedback
- 33+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math-content review
- 4deep knowledge of algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs
- 5ability to evaluate math content against rubrics and identify issues such as incorrect assumptions, flawed reasoning, or incomplete explanations
- 6comfort reviewing both conceptual explanations and step-by-step solutions and assessing logical progression
- 7familiarity with math tools/workflows such as latex, python, matlab, r, wolframalpha/mathematica, geogebra, desmos, or spreadsheet modeling
- 8experience leading or supporting remote teams of trainers, annotators, reviewers, educators, or qas
- 9proficiency with fast-moving remote environments using discord, google sheets/docs, trackers, dashboards, and project management systems
- 10highly detail-oriented and organized; able to maintain style guides, trackers, onboarding materials, calibration tasks, and QA documentation
- 11experience with ai training, data annotation, large language models, prompt/response evaluation, mathematical content qa, or rubric-based llm evaluation is a strong plus
- 12native fluency in punjabi
Who Should Apply
Ideal candidates hold an advanced degree in mathematics or a closely related field and bring at least 3 years of experience in math QA, education, or research. You excel at dissecting math content against rubrics, spotting gaps in reasoning, and delivering clear, actionable English feedback. This role fits detail-oriented professionals who can coordinate with distributed teams and maintain rigorous documentation. It may be less suitable for applicants lacking Punjabi fluency, AI training data QA exposure, or remote-team leadership experience.
Salary Insight
Pay: $75/hr (hourly). This contract role aligns with mid-senior level mathematics quality leadership and remote collaboration on AI training projects.
Location
Required Skills
Application Tip
Include a concise sample of rubric-based feedback on a math item that demonstrates your ability to identify a flaw and provide a corrected solution with LaTeX notation.
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1Application received
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