Dart QA Lead

As a Dart QA Lead, you will review AI-generated Dart code and trainer QA work. You will check whether code is correct, type-safe, readable, maintainable, efficient, properly tested, and aligned with the instructions and project rubric.

You will also give clear written feedback, answer technical questions, maintain Dart guidance and QA materials, and support onboarding and quality improvement for Dart contributors.

• Review Dart code, Flutter snippets, debugging answers, tests, and technical explanations.
• Check syntax, null safety, asynchronous behavior, Flutter usage, packages, tests, and rubric interpretation.
• Find type errors, flawed logic, incorrect async handling, weak null-safety practices, made-up APIs, and incomplete explanations.
• Flag insecure, misleading, non-executable, or non-production-ready Dart and Flutter recommendations.
• Create and maintain style guides, examples, trackers, FAQs, calibration tasks, onboarding materials, and other QA documentation.
• Communicate guideline changes and Dart-specific standards.
• Support onboarding and training calls for Dart contributors.
• Help address recurring QA gaps and contributor activation follow-ups.

This is a remote, part-time contractor role for candidates in the United States. The work requires at least 20 hours per week and strong English communication for clear technical feedback.

• Pay: Up to $65 per hour.
• Location: United States only.
• Schedule: 20 or more hours per week.
• Work type: Remote contractor and part-time.
• Strong Dart and Flutter knowledge, including syntax, null safety, classes, mixins, extensions, generics, collections, futures, streams, isolates, packages, and error handling.
• Familiarity with widgets, state management, pub.dev packages, unit testing, widget testing, integration testing, build tools, mobile app architecture, GitHub, and CI/CD.
• Experience leading or supporting remote teams of trainers, engineers, reviewers, or QA professionals is strongly preferred.
• Experience with AI training, large language model evaluation, code QA, or rubric-based code review is a strong plus.
• A bachelor's or master's degree in computer science, software engineering, or information technology, or equivalent professional experience.
• Comfort using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Strong organization skills for maintaining guides, trackers, FAQs, calibration tasks, and onboarding materials.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind modern AI systems, including reviewing code and rating model responses. Experienced reviewers help identify errors and improve the quality, safety, and usefulness of what AI produces.