SME AI Training Jobs - Compare Pay

SME

IntelliJ IDEA Specialist

SMESoftware, AI and Data

Up to $25/hr

Apply

About this role

In this hourly, remote contractor role, you will work as an IntelliJ IDEA Specialist (SME) to create realistic, challenging computer-based tasks using IntelliJ IDEA and related software development workflows. You will design practical IDE tasks, document them clearly in SuperAnnotate, ensure your setup supports the task, and record yourself executing the task on your computer. Tasks may include creating Java/Kotlin projects, configuring SDKs, running and debugging code, using Maven or Gradle, managing packages, refactoring, using Git integration, navigating code, writing tests, or troubleshooting build issues. Your work will help train advanced AI models to better understand how real users complete software development workflows in IntelliJ IDEA. 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 IntelliJ IDEA expertise directly helps improve the world’s premier AI models by teaching them how real users complete practical coding, debugging, and project-management tasks in a professional IDE. Requirements - Hands-on experience using IntelliJ IDEA for Java, Kotlin, backend development, debugging, project setup, refactoring, build tools, or Git workflows. - English proficiency at B2 level or higher to understand project instructions, document tasks clearly, and communicate with the project team. - Comfortable using a computer, managing files, opening projects, configuring SDKs, installing dependencies, and recording workflows. - Ability to come up with realistic and challenging IntelliJ IDEA tasks that reflect actual coding, debugging, testing, build, or project-setup use cases. - Strong understanding of IntelliJ IDEA basics such as project structure, SDKs, run configurations, debugger, refactoring, Maven/Gradle, terminal, code navigation, and version control. - Ability to ensure your setup supports the task, including having IntelliJ IDEA installed, projects/files available, SDK configured, dependencies installed, and references ready before recording. - High attention to detail when preparing the task, executing the workflow, and checking that the recording is complete and understandable. - Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. - Additional professional skills are appreciated, including Java, Kotlin, backend development, QA, GitHub, DevOps, technical writing, coding, or other computer-based workflows. Responsibilities - Create realistic IntelliJ IDEA tasks: Come up with realistic and challenging tasks that can be executed on the computer using IntelliJ IDEA, then document the task clearly in SuperAnnotate. - Prepare the work environment: Ensure your setup supports the task, including having IntelliJ IDEA installed, projects/files available, SDK configured, dependencies installed, and any required references ready before recording. - Record task execution: Record yourself executing the IntelliJ IDEA task on your computer while following project instructions and ensuring the workflow is clear, complete, and realistic. - Document task context: Provide enough task context, steps, goals, project files, dependencies, and notes so reviewers can understand what the task is and how it was completed. - Demonstrate practical software use: Complete workflows involving coding, debugging, refactoring, Maven/Gradle builds, tests, terminal use, Git integration, project setup, or troubleshooting where relevant. - Maintain submission quality: Review your recording and documentation before submission to ensure the task is complete, understandable, realistic, and aligned with project guidelines. Skills - IntelliJ IDEA - Git - IDE - Kotlin - Java - Screen Recording - Maven - Gradle - English - Debugging Additional skills - IntelliJ IDEA - Java - Kotlin - Backend Development - Spring Boot - JVM Debugging - IntelliJ Debugger - Run/Debug Configurations - Refactoring - Code Navigation - Project Structure - SDK Configuration - Maven - Gradle - Dependency Management - Unit Testing - JUnit - Git - Git Workflows - GitHub - Version Control - Terminal - Code Review - Technical Writing - Software Troubleshooting - Build Automation - Continuous Integration - DevOps - Remote Collaboration - English (B2)

SME

Biologist

SMELife Sciences

Up to $70/hr

17 countries

Apply

About this role

We’re seeking biologists to join our AI training project. In this role, you will review AI-generated responses, evaluate reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology or conceptual understanding; fact-check biological information; write high-quality biological explanations and model solutions that demonstrate correct methods; and rate and compare multiple AI responses based on biological correctness and reasoning quality. 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. Requirements - You hold a MS or PhD in Biology, Molecular Biology, Biochemistry, Physiology, or a closely related life-science field.in one of the top 100 universities. - Confident in human and animal biology, molecular pathways, physiology, disease/health fundamentals, and lab/experimental reasoning. - You have developed or critically reviewed complex biology content (e.g., problem banks, proofs, textbook sections, research notes). - Expert at fact-checking information using public sources across multiple domains. - Published in a peer-reviewed journal. - You communicate biology clearly and turn advanced theory into real-world solutions. - English proficiency C1 and above with excellent writing skills. - Bonus: Data labeling, RLHF, or AI model evaluation experience. Responsibilities - Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects. - Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance. - Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases. Skills - Research - Computational Biology - Evolutionary Biology - Molecular Biology - Cell Biology - Biology - Wildlife Biology - Cellular Biology - Systems Biology - English Additional skills - Molecular Biology - Cell Biology - Biochemistry - Physiology - Human Biology - Animal Biology - Genetics - Genomics - Proteomics - Bioinformatics - Molecular Pathways - Disease Biology - Immunology - Microbiology - Neuroscience - Pharmacology - Experimental Design - Laboratory Techniques - PCR - qPCR - Western Blotting - ELISA - Cell Culture - Microscopy - Flow Cytometry - Statistical Analysis - Scientific Writing - Peer Review - Literature Review - Fact-Checking - AI Model Evaluation

SME

Persian Team Lead

SMELanguages / Business and Consulting

Up to $25/hr

Apply

About this role

In this hourly, remote contractor role, you will work as an Insurance Subject Matter Expert (SME) to review AI-generated insurance responses and/or create expert insurance content, evaluating reasoning quality and step-by-step decision-making while providing precise written feedback. You will assess solutions for accuracy, clarity, regulatory/compliance awareness, and adherence to the prompt; identify errors in policy interpretation, coverage analysis, claims handling logic, underwriting reasoning, risk assessment, exclusions/endorsements, and terminology; fact-check technical insurance information; write high-quality explanations and model solutions that demonstrate correct methods; and rate and compare multiple responses based on correctness and reasoning quality. 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. 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. Requirements - Bachelor’s degree (or higher) in Business, Finance, Risk Management, Insurance, Law, or a related field (or equivalent professional experience). - 5+ years of professional experience in insurance (claims, underwriting, brokerage, actuarial support, risk management, compliance, or operations). - Strong understanding of insurance fundamentals: policy structure (insuring agreement, definitions, conditions, exclusions), endorsements, limits/deductibles, and coverage triggers. - Comfortable with coverage and claims reasoning across one or more lines (e.g., P&C, commercial lines, auto, homeowners, liability, health, life). - Ability to evaluate decisions for internal consistency (facts → policy language → coverage position → documentation), including edge cases and ambiguity. - Strong attention to detail when identifying missing facts, incorrect assumptions, misapplied definitions, or unsafe/unsupported recommendations; minimum C1 English proficiency. - Clear written communication skills, including the ability to explain complex policy concepts in plain language. - Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. - Professional designations (e.g., CPCU, AINS, ARM, CIC, AU) are a plus. - Prior experience with AI data training/annotation, claims QA, underwriting QA, policy drafting/review, or insurance editorial work is strongly preferred. Responsibilities - Develop AI Training Content: Create detailed prompts and gold-standard outputs across coverage analysis, claims scenarios, underwriting decisions, and policy communication. - Optimize AI Performance: Evaluate and rank AI responses to improve correctness, completeness, clarity, and compliance-aware reasoning. - Ensure Model Integrity: Test AI outputs for inaccuracies, misleading guidance, inappropriate certainty, and bias; validate reliability across use cases. Skills - Insurance Coverage - Customer Communication - Loss Prevention - Regulation - Underwriting - Claims Handling - Risk Assessment - Compliance - Exclusions And Endorsements - Policy Interpretation - English Additional skills - Insurance Underwriting - Claims Management - Policy Interpretation - Coverage Analysis - Policy Drafting - Policy Review - Endorsements - Limits & Deductibles - Coverage Triggers - Commercial Lines Insurance - Personal Lines Insurance - Property & Casualty (P&C) - General Liability - Auto Insurance - Homeowners Insurance - Life Insurance - Health Insurance - Risk Management - Insurance Compliance - Regulatory Compliance - Insurance Operations - Brokerage - Actuarial Support - Claims QA - Underwriting QA - Insurance Documentation - Technical Writing - Contract Analysis - AI Data Annotation - CPCU

SME

Gujarati Expert with Mathematical Background

SMELanguages / STEM

Up to $20/hr

About this role

As an Android Engineer (Kotlin / Java), you will work remotely on an hourly paid basis to review AI-generated Android code, mobile architectures, and technical explanations, as well as produce high-quality reference implementations and step-by-step reasoning for complex engineering problems. You will assess solutions for correctness, clarity, security, performance, reliability, and adherence to the prompt; identify issues in Jetpack Compose/UI, concurrency, threading, memory/performance, app lifecycle, networking, persistence, and build/release practices; fact-check technical information; write high-quality explanations and model solutions that demonstrate best practices; and rate and compare multiple AI responses based on correctness and reasoning quality. This fully remote, hourly paid contractor role is with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs—where your frontend expertise will directly help improve the world’s premier AI models used by millions of developers worldwide. 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. Requirements - Bachelor’s degree or higher in Computer Science, Software Engineering, or a closely related technical field (or equivalent practical experience). - 4+ years of professional experience building production Android apps, including work in Kotlin and (ideally) Java codebases. - Expert-level proficiency in Kotlin (Kotlin 1.6+): null-safety, coroutines/flows, sealed types, generics, and idiomatic patterns. - Strong Android fundamentals: app lifecycle, Activities/Fragments, state restoration, background execution limits, and permissions. - Modern UI experience with Jetpack Compose and/or Views; ability to reason about recomposition, state hoisting, and UI performance. - Concurrency expertise: coroutines, Flow, threading best practices, cancellation, and avoiding race conditions/ANRs. - Strong knowledge of architecture patterns: MVVM, Clean Architecture concepts, dependency injection (Hilt/Dagger/Koin), and modularization. - Experience with networking and data: Retrofit/OkHttp, serialization, caching, offline strategies, and persistence (Room/SQLite/DataStore). - Experience with testing and quality: JUnit, instrumentation tests, Compose UI tests/Espresso, mocking strategies, CI/CD (Gradle, Play Console workflow). - Security awareness: secure storage (Keystore/EncryptedSharedPreferences), auth flows, certificate pinning awareness, privacy permissions, and sensitive data handling. - Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines. - Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus. - Highly detail-oriented and systematic, with a methodical approach to evaluating reasoning quality and identifying subtle issues in complex Android code. Responsibilities - Develop AI Training Content: Create detailed prompts across Android topics and write high-quality reference answers to guide AI learning. - Optimize AI Performance: Evaluate and rank AI responses to enhance correctness, security, performance, and maintainability. - Ensure Model Integrity: Test AI outputs for inaccuracies or unsafe recommendations, validating reliability across real-world Android use cases. Skills - Clean Architecture - Code Review - Coroutines - Networking - Performance Optimization - Kotlin - Java - Jetpack Compose - App Architecture - Android - MVVM - Debugging Additional skills - Kotlin - Java - Android SDK - Jetpack Compose - Android Views - Coroutines - Kotlin Flow - MVVM - Clean Architecture - Dependency Injection - Hilt - Dagger - Koin - Modularization - Gradle - Android Studio - App Lifecycle - Activities & Fragments - State Restoration - Background Execution - Permissions - Retrofit - OkHttp - Serialization - Caching - Offline-First - Room - SQLite - DataStore - JUnit - Espresso

SME

Materials Scientist

SMESTEM

Up to $40/hr

Up to $70/hr

United States

Apply

About this role

In this hourly, remote contractor role, you will work as an Earth Sciences / Geology Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across geology and earth science AI training projects. You will review AI-generated earth science/geology 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 scientific accuracy, geologic reasoning, terminology quality, spatial and temporal context, unit handling, data interpretation, 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 earth science/geology expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert 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 earth science/geology quality leadership will directly help improve the world’s premier AI models by ensuring that geology and earth science training data is accurate, contextualized, 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. Requirements - Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback. - 3+ years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related workflows. - Strong understanding of plate tectonics, rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes. - Ability to evaluate earth science/geology content against detailed rubrics and identify issues such as incorrect geologic processes, wrong timescales, misleading causal claims, flawed map/data interpretation, unsupported environmental claims, or oversimplified explanations. - Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization is preferred. - Experience leading or supporting remote teams of researchers, educators, reviewers, environmental specialists, annotators, 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, calibration tasks, and documentation. - Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus. Responsibilities - Quality monitoring: Spot-check geology/earth science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. - Scientific review: Evaluate AI-generated geology explanations, earth science summaries, geologic process descriptions, map/data interpretations, climate or hazard explanations, and step-by-step reasoning for accuracy and clarity. - Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and geology/earth-science-specific review standards. - Question handling: Respond to trainer/QA questions clearly and promptly, especially around geologic timescales, rock/mineral identification, earth systems, natural hazards, spatial reasoning, environmental interpretation, 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 geology/earth science 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 geology/earth-science-specific review requirements. - Quality alignment: Ensure all trainers and QAs apply geology/earth science review guidelines consistently and understand updates as projects evolve. - Risk review: Flag misleading, overconfident, geologically impossible, environmentally unsupported, or poorly contextualized earth science claims. - Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for earth science/geology AI training projects. Skills - Climate Systems - LLM Evaluation - Earth Sciences - Geology - Mineralogy - Plate Tectonics - AI Training - Geoscience - Trainer Feedback - Scientific Review Additional skills - Quality Assurance - Geology - Earth Sciences - Environmental Science - Geoscience - Geospatial Analysis - GIS - Remote Sensing - Geologic Mapping - Field Methods - Stratigraphy - Structural Geology - Mineralogy - Plate Tectonics - Geomorphology - Hydrology - Geochemistry - Core Logging - Well Log Interpretation - Natural Hazards - Climate Science - Earth System Science - Data Interpretation - Scientific Writing - Technical Editing - Rubric-Based Review - Academic Peer Review - Data Annotation - LLM Evaluation - Python

SME

Odia (Oriya) Language Expert

SMELanguages / Education and Humanities

Up to $15/hr

Apply

About this role

In this hourly, remote contractor role, you will work as an Odia (Oriya) Language Specialist (SME) to review AI-generated Odia content and/or create high-quality Odia reference content, evaluating language quality and step-by-step reasoning while providing precise written feedback. You will assess outputs for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, and adherence to the prompt; identify errors in meaning, mistranslation, register (formal vs informal), ambiguity, and logical consistency; fact-check claims when needed; write high-quality rewrites and model answers that demonstrate best practices in Odia writing; and rate and compare multiple AI responses based on correctness and overall quality. 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 Odia expertise directly helps improve the world’s premier AI models by making their Odia language output more natural, reliable, culturally accurate, and clearly written. Requirements - Bachelor’s degree (or higher) in Linguistics, Odia/English Literature, Communications, Journalism, Translation, or a related field (or equivalent professional experience). - Native or near-native Odia proficiency (reading and writing required). - Strong professional proficiency in English (minimum C1) to follow guidelines and provide detailed feedback in English. - 3+ years of professional experience in writing, editing, localization, translation, content QA, journalism, education, or related language-focused work. - Deep understanding of Odia grammar, spelling conventions, punctuation, and style—able to explain why something is wrong and how to fix it. - Comfortable handling multiple registers (formal/informal), regional variation within Odisha, and audience adaptation (India vs diaspora). - High attention to detail when spotting subtle meaning shifts, awkward literal translations, hallucinated claims, or culturally mismatched phrasing. - Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. - Prior experience with AI data training/annotation, translation QA, editorial QA, or rubric-based evaluation is strongly preferred. Responsibilities - Develop AI Training Content: Create prompts and gold-standard Odia answers across multiple domains (general knowledge, customer support, education, conversational writing). - Optimize AI Performance: Evaluate and rank AI outputs to improve fluency, correctness, tone match, and cultural appropriateness. - Ensure Model Integrity: Detect unsafe or misleading content, factual hallucinations, bias, and policy-risk language; validate reliability across use cases. Skills - Style - Copyediting - Translation Quality Review - Localization - Odia (Oriya) - Fact-Checking - Tone & Register - English - Proofreading - Cultural Context - Grammar Additional skills - Odia (Oriya) Language Proficiency - Odia Grammar - Odia Proofreading - Odia Copyediting - English (C1) Proficiency - Translation (Odia-English) - Localization - Transcreation - Linguistics - Terminology Management - Style Guide Adherence - Content Quality Assurance (QA) - Translation Quality Assessment (TQA) - Editorial QA - AI Data Annotation - LLM Response Evaluation - Rubric-Based Evaluation - Natural Language Understanding (NLU) - Text Classification - Entity Annotation - Error Analysis - Fact-Checking - Cultural Localization - Regional Dialect Knowledge (Odisha) - Audience Adaptation - Journalism Writing - Technical Writing - Subtitling - CAT Tools - Microsoft Office - Remote Collaboration

SME

SMELanguages / Business and Consulting

Up to $35/hr

China

Apply

About this role

In this hourly, remote contractor role, you will work as a Chinese (Simplified) Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Simplified Chinese AI training projects for Mainland China. You will review AI-generated Simplified Chinese 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 accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, 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 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 Simplified Chinese quality leadership will directly help improve the world’s premier AI models by ensuring that Chinese training data is natural, accurate, culturally appropriate, 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. Requirements - Bachelor’s or Master’s degree in Chinese, Mandarin, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field. - Native or near-native Simplified Chinese proficiency, with strong Mainland China Mandarin writing judgment. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English. - 3+ years of professional experience in Simplified Chinese writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows. - Strong understanding of Simplified Chinese grammar, punctuation, terminology, register, tone, Mainland China Mandarin usage, cultural context, and localization expectations. - Ability to evaluate Simplified Chinese content against detailed rubrics and identify issues such as mistranslation, Traditional Chinese leakage, unnatural tone, Taiwan/Hong Kong terminology mismatch, hallucinated claims, ambiguity, or inconsistent terminology. - Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred. - Comfortable with 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, and documentation. - Experience with AI training, data annotation, LLM evaluation, prompt/response evaluation, or rubric-based LLM QA is a strong plus. Responsibilities - Spot-check Simplified Chinese items, identify issues, provide feedback through DMs, and escalate recurring or critical quality problems. - Update trainers and QAs on Discord about new guidelines, workflow updates, project changes, and quality expectations. - Respond to questions around Simplified Chinese wording, Mainland China terminology, punctuation, register, translation fidelity, cultural context, and edge cases. - DM inactive contributors, encourage activation, track follow-ups, and flag availability issues. - Create and maintain Simplified Chinese documentation, style guides, trackers, FAQs, examples, honeypots, and onboarding materials. - Run onboarding/training calls for Simplified Chinese contributors. - Ensure Mainland China Simplified Chinese guidelines are applied consistently. - Identify recurring quality gaps and build scalable QA processes. Skills - LLM Evaluation - Mandarin - Translation Quality Review - Style Guides - Chinese Quality Assurance - AI Training - Simplified Chinese - English - Mainland China - Localization QA Additional skills - Simplified Chinese (Mainland) - Mandarin Chinese - English Proficiency - Localization QA - Linguistic QA (LQA) - Translation - Editing & Proofreading - Chinese Grammar & Punctuation - Terminology Management - Style Guide Development - Glossary Management - Cultural Localization - Tone & Register Adaptation - Content Quality Assurance - Rubric-Based Evaluation - LLM Evaluation - AI Training Data QA - Data Annotation - Prompt/Response Review - Machine Translation Post-Editing (MTPE) - Annotation Guidelines - Reviewer Training & Onboarding - Remote Team Leadership - Quality Auditing - Issue Tracking - Google Sheets - Google Docs - Discord - Project Management Tools - Documentation Writing

SME

TypeScript Team Lead

SMESoftware, AI and Data / Business and Consulting

Up to $70/hr

United States

Apply

About this role

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. Requirements - 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. 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. Skills - LLM Evaluation - Type Safety - Code Review - TypeScript - AI Training - Frontend Development - Node.js - Trainer Feedback - Debugging - TypeScript QA Additional skills - TypeScript - JavaScript (ES6+) - Node.js - React - Next.js - Express.js - NestJS - Full-Stack Development - Frontend Engineering - Backend Development - Type-Safe API Design - REST APIs - Async/Await - Promises - Event Loop - Git - GitHub - GitHub Actions - Code Review - Technical Leadership - Mentoring - Remote Team Leadership - Software QA - Test Automation - Jest - Vitest - Playwright - ESLint - Prettier - Webpack - Vite

SME AI training jobs. Earn on your schedule.

Browse by field

Platforms

Get this week’s AI training jobs

Filters

Job listings367

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role