Role Description
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 JavaScript quality leadership will directly help improve the world’s premier AI models by ensuring that JavaScript training data is accurate, executable, logically sound, clearly explained, well-documented, and aligned with client expectations.
In this hourly, remote contractor role, you will work as a JavaScript Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across JavaScript AI training projects. You will:
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Review AI-generated JavaScript code and trainer/QA work.
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Evaluate output quality against project guidelines.
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Provide precise written feedback.
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Ensure that all contributors follow the expected quality standards.
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Assess work for code correctness, reasoning quality, runtime behavior, debugging accuracy, readability, maintainability, performance, security awareness, test coverage, formatting, instruction-following, and adherence to project-specific rubrics.
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Spot recurring quality issues and communicate updates to trainers and QAs.
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Support onboarding, maintain documentation, and help activate contributors who are not working consistently.
Quality monitoring includes:
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Spot-checking JavaScript items and identifying quality issues.
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Providing ongoing feedback through DMs.
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Escalating recurring or critical issues.
Code review involves:
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Evaluating AI-generated JavaScript code, debugging responses, implementation explanations, algorithmic solutions, frontend/backend snippets, tests, and step-by-step reasoning for correctness and clarity.
Trainer and QA communication tasks include:
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Updating trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and JavaScript-specific review standards.
Question handling requires:
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Responding to trainer/QA questions clearly and promptly.
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Addressing queries around JavaScript behavior, async logic, browser vs Node.js environments, frameworks, package usage, testing, edge cases, and rubric interpretation.
Trainer/QA activation management involves:
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DMing contributors who are inactive or not working.
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Encouraging activation and tracking follow-ups.
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Flagging availability issues when needed.
Documentation tasks include:
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Creating and maintaining JavaScript project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
Onboarding and training responsibilities include:
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Scheduling and running onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and JavaScript-specific review requirements.
Quality alignment ensures:
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All trainers and QAs apply JavaScript review guidelines consistently and understand updates as projects evolve.
Risk and security review involves:
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Flagging unsafe, misleading, insecure, or overconfident code recommendations, especially around injection risks, dependency usage, authentication, browser security, data handling, and production readiness.
Process improvement includes:
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Identifying recurring quality gaps.
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Proposing workflow improvements.
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Helping build scalable QA processes for JavaScript AI training projects.
Qualifications
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Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a closely related field; equivalent professional software engineering experience may be considered.
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Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English.
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3+ years of professional experience in JavaScript development, frontend engineering, backend development with Node.js, full-stack engineering, code review, software QA, technical mentoring, or related workflows.
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Strong understanding of core JavaScript concepts such as closures, scope, hoisting, prototypes, promises, async/await, event loop, modules, DOM manipulation, error handling, data structures, and modern ECMAScript features.
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Ability to evaluate JavaScript content against detailed rubrics and identify issues such as incorrect logic, non-executable code, flawed reasoning, missing edge cases, poor async handling, security risks, performance problems, hallucinated APIs, or incomplete explanations.
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Familiarity with common JavaScript ecosystems and tools such as Node.js, npm/yarn/pnpm, React, Vue, Express, Jest, Mocha, Playwright, ESLint, Prettier, Vite, Webpack, Babel, or browser developer tools is preferred.
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Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, coding mentors, or QAs is strongly preferred.
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Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.
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Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
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Experience with AI training, data annotation, large language models, prompt/response evaluation, code content QA, or rubric-based LLM evaluation is a strong plus.
Benefits
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💰 Up to $70/hour
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🌍 Remote
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👥 200+ Openings
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Be a part of a forward-thinking team and help us train AI to communicate more effectively.
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Your work directly contributes to how AI systems learn and communicate.
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Your Schedule, Your Rules: Set your own hours and work around your life.
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Weekly Pay: Receive fast, reliable payments once work is approved.
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Community Rewards: Get rewarded for referrals with ongoing bonus income.
