Mathematics Quality Assurance Lead (QAL)

SME Careers; Himachal Pradesh; Remote; INR 1,240,000 - 2,066,000; Part time

Job summary

SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, seeks a Mathematics Quality Assurance Lead (QAL) for an hourly, remote contractor role. You will oversee quality across mathematics AI training projects, review AI-generated math content, and guide trainers and QAs to meet strict rubrics.

You will coordinate feedback, maintain documentation, and help onboard new contributors while ensuring accuracy, logical reasoning, and clear explanations.

Qualifications

• Bachelor’s, Master’s, or PhD in Mathematics or related field.
• Strong English to follow guidelines and provide clear feedback.
• 3+ years in mathematics, teaching, research, or math-content review.

Responsibilities

• Quality monitoring: spot-check items and provide feedback.
• Mathematical review: evaluate explanations, proofs, derivations, and solutions.
• Trainer/QA communication: update on guidelines and rubrics via Discord.
• Question handling: respond clearly on reasoning validity and notation.
• Activation management: DM inactive contributors and track follow-ups.
• Documentation: maintain style guides, FAQs, trackers, onboarding materials.
• Onboarding and training: run onboarding calls and explain expectations.
• Quality alignment: ensure consistent application of mathematics guidelines.
• Error-pattern analysis: identify recurring issues and gaps.
• Process improvement: propose scalable QA workflows for math training.

Skills

Mathematics expertise

Quality assurance leadership

English communication

Attention to detail

Remote team management

Education

Bachelor’s/Master’s/PhD in Mathematics or related field

Tools

LaTeX

Python

MATLAB

R

WolframAlpha/Mathematica

GeoGebra

Desmos

Spreadsheet modeling

Symbolic computation tools

Job description

In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead (QAL) 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 with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, 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.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Key Responsibilities

• Quality monitoring: Spot-check mathematics items, identify quality issues, provide ongoing feedback through DMs, and elevate 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.

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.
• Native fluency in Punjabi