Mathematics Quality Assurance Lead (QAL)

About the Role

This is a remote, hourly contractor role for a Mathematics Quality Assurance Lead (QAL) responsible for overseeing quality, consistency, and contributor performance across mathematics AI training projects.

You will review AI-generated mathematics content, evaluate trainer and QA work, provide detailed feedback, maintain quality standards, support onboarding efforts, and ensure compliance with mathematical review guidelines and project rubrics.

The role combines mathematical expertise, quality assurance, AI evaluation, contributor management, documentation, and process improvement.

Key Responsibilities

Quality Monitoring

• Review mathematics training items and QA outputs
• Identify recurring quality issues and mathematical errors
• Provide actionable feedback to contributors
• Escalate critical quality concerns

Mathematical Review

Evaluate AI-generated mathematical explanations, proofs and derivations, algebraic solutions, geometry problems, calculus solutions, linear algebra reasoning, probability and statistics problems, discrete mathematics content, number theory solutions, combinatorics reasoning, differential equations solutions, and step-by-step reasoning workflows.

Verify mathematical accuracy, logical validity, proof correctness, calculation accuracy, notation consistency, completeness of reasoning, instruction compliance, and clarity of explanation.

Trainer & QA Communication

• Communicate guideline updates and workflow changes
• Clarify mathematics-specific review standards
• Maintain contributor alignment

Question Resolution

Respond to contributor questions regarding mathematical reasoning, proof validity, notation standards, assumptions and constraints, solution methods, derivations, formatting expectations, and rubric interpretation.

Contributor Activation Management

• Follow up with inactive contributors and track engagement
• Encourage participation and task completion

Documentation Management

Create and maintain style guides, mathematics FAQs, quality notes, calibration tasks, examples, trackers, honeypots, and onboarding materials.

Onboarding & Training

• Conduct onboarding and training sessions
• Explain project workflows, evaluation rubrics, mathematics quality standards, proof-review expectations, and reasoning quality requirements

Error Pattern Analysis

Identify recurring issues such as skipped reasoning steps, invalid simplifications, incorrect formulas, proof gaps, arithmetic errors, algebraic mistakes, notation inconsistencies, unsupported conclusions, and incomplete derivations.

Process Improvement

• Identify recurring quality gaps and recommend workflow improvements
• Help build scalable QA processes for mathematics projects

Required Skills & Qualifications

• Bachelor's, Master's, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or related quantitative discipline
• 3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, curriculum development, assessment design, or mathematics content review
• Strong understanding of algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs
• Ability to identify incorrect assumptions, flawed reasoning, invalid proofs, calculation errors, notation issues, missing steps, hallucinated facts, and logical inconsistencies
• Strong written English, mathematical feedback, and documentation skills

Preferred Qualifications

• Experience with LaTeX, Python, MATLAB, R, Mathematica, WolframAlpha, GeoGebra, Desmos, or spreadsheet modeling
• Experience leading or supporting educators, trainers, reviewers, QA teams, or annotation teams
• Experience with AI training, data annotation, LLM evaluation, or rubric-based QA
• Familiarity with Discord, Google Docs, Google Sheets, and project management systems

Additional Information

• Fully remote — Flexible schedule — Weekly payments
• Access to future opportunities through the SME Careers expert network

About SME Careers

SME Careers is an AI data services company and subsidiary of SuperAnnotate that provides training data for leading AI companies and foundation-model laboratories.