The work
You will create and review technical content used to train AI models. The work applies practical iOS engineering judgment to mobile development problems and helps models produce accurate, useful solutions.
You will work on questions and case studies covering iOS development, then assess AI responses for accuracy, completeness, and alignment with sound development practices.
- Create iOS development questions and case studies involving UI development, state management, networking, data persistence, memory management, app lifecycle, and debugging.
- Evaluate AI-generated answers for technical accuracy, completeness, and quality.
- Write detailed feedback that improves AI-generated answers and their educational value.
- Refine question difficulty and content quality with other mobile development and technical experts.
- Assess scenarios involving UI and user experience implementation and mobile application architecture.
What it pays and takes
This is a remote, part-time contract role.
- Pay: $70 per hour.
- Time: 20 or more hours per week.
- Location: Remote and open to candidates in the countries listed for this role.
- Language: Fluent in English.
- Experience: Proven experience developing iOS applications with Swift.
- Technical knowledge: Swift syntax, UIKit or SwiftUI, the iOS SDK, and common mobile development patterns.
- Core skills: Strong analytical, written, and verbal communication skills, plus close attention to technical detail.
- Helpful background: MVVM, MVC, VIPER, Combine, async/await, Core Data, or third-party iOS libraries.
- Additional useful experience: Published App Store applications, open source iOS work, technical writing, Xcode, Interface Builder, debugging tools, performance optimization, mobile technology initiatives, or AI and machine learning integration in iOS applications.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work uses human-written examples, reviews, and feedback to help computer systems understand code and produce better answers. Experienced specialists are valuable because they can judge whether technical content is accurate, complete, and useful in real work.