TypeScript Quality Assurance Lead (QAL)
SME Careers • The United States
Education
Any
Type
Pay Rate
$70/task
Listed
Today
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In this hourly, remote contractor role, you will work as a TypeScript Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across TypeScript AI training projects. You will review AI-generated TypeScript code 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 code correctness, type safety, reasoning quality, runtime behavior, debugging accuracy, readability, maintainability, performance, security awareness, test coverage, 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 TypeScript 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 TypeScript quality leadership will directly help improve the world’s premier AI models by ensuring that TypeScript training data is accurate, type-safe, executable, 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.
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.
### Key Responsibilities
- Quality monitoring: Spot-check TypeScript items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
- Code review: Evaluate AI-generated TypeScript code, type definitions, debugging responses, implementation explanations, frontend/backend snippets, tests, and step-by-step reasoning for correctness, type safety, and clarity.
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and TypeScript-specific review standards.
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around type safety, inference, generics, strict mode, async logic, browser vs Node.js environments, frameworks, testing, edge cases, 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 TypeScript 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 TypeScript-specific review requirements.
- Quality alignment: Ensure all trainers and QAs apply TypeScript review guidelines consistently and understand updates as projects evolve.
- Risk and security review: Flag unsafe, misleading, insecure, or overconfident code recommendations, especially around type bypassing, unsafe casts, dependency usage, authentication, data handling, and production readiness.
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for TypeScript AI training projects.
### Your Profile
- 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.
- Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English.
- 3+ years of professional experience in TypeScript development, JavaScript development, frontend engineering, backend development with Node.js, full-stack engineering, code review, software QA, technical mentoring, or related workflows.
- Strong understanding of core TypeScript concepts such as static typing, interfaces, type aliases, generics, unions/intersections, narrowing, inference, mapped types, conditional types, utility types, strict mode, module systems, and type-safe API design.
- Strong understanding of JavaScript runtime behavior, including promises, async/await, event loop, closures, scope, modules, error handling, and modern ECMAScript features.
- Ability to evaluate TypeScript content against detailed rubrics and identify issues such as incorrect logic, non-executable code, type errors, unsafe any usage, flawed reasoning, missing edge cases, poor async handling, security risks, hallucinated APIs, or incomplete explanations.
- Familiarity with common TypeScript ecosystems and tools such as Node.js, React, Next.js, Express/NestJS, npm/yarn/pnpm, Jest, Vitest, Playwright, ESLint, Prettier, Vite, Webpack, tsconfig, or GitHub workflows is preferred.
- Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, coding mentors, or QAs is strongly preferred.
- Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, 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, code content QA, or rubric-based LLM evaluation is a strong plus.
Requirements
- Advanced degree or strong hands-on professional experience in the domain
- Ability to pass domain-specific qualification assessments
- Eligible to create a verified account on Deel (for payments/compliance)
- Proficiency in English (for instructions and feedback)
- Must be located in one of the 40+ supported countries (e.g., The United States)
Compensation Analysis
Don't just label data—build a career. SME Careers is unique in the AI training space because it offers a transparent growth ladder. High performers aren't just kept in the queue; they are promoted to Quality Analysts and Project Managers. With weekly transparent payments via Deel and the freedom to work on your own schedule, this is built for modern experts who want long-term engagement.
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Frequently Asked Questions
Is there room for advancement?
Yes. This is a key feature of the platform. They explicitly list a career path: Data Trainer -> Quality Analyst -> QA Lead -> Project Manager. Consistent high-quality work can lead to leadership roles.
How do payments work?
Payments are processed weekly through Deel. This ensures tax compliance and allows them to hire freelancers from over 40 countries securely.
Is the work ongoing or project-based?
Work is project-based, which means assignments can vary in duration and availability. However, top performers often get priority access to new projects.
What does the work actually look like?
It is practical, hands-on data work. You might be recording short videos, categorizing images, rating text responses, or analyzing data. The tasks are designed to be short and distinct—typically 5-60 minutes per task.
How flexible is the schedule?
Extremely. This is true "log in and work" flexibility. You can usually work for 20 minutes or 4 hours depending on your availability. There are rarely minimum hour requirements, making it ideal for side income.
Is there an interview?
Usually, no. Hiring for these roles is almost entirely based on passing an automated assessment or "qualification" task. If you pass the test, you get access to the work.
Who is behind SME Careers?
SME Careers is the expert talent division of SuperAnnotate, a leading AI data infrastructure platform. They connect domain experts with high-level AI training projects.