Swift Engineer LLM Code Reviewer

You will review AI-generated Swift code and written model responses for an AI training project focused on iOS development. Your feedback will help improve how AI systems produce and explain mobile application code.

• Evaluate model outputs using project rubrics and record evidence-based judgments.
• Review source materials and AI-generated code against project guidelines.
• Assess correctness, maintainability, performance, app logic, mobile architecture, and UI logic quality.
• Explain technical judgments clearly in written feedback.
• Maintain consistent quality across repeated code review tasks.

This is remote, part-time contractor work with flexible scheduling. The project is estimated to run for 1 to 3 months.

• $55 per hour.
• About 20 hours per week.
• Estimated project earnings of $8,800 based on the listed schedule and duration.
• Open to candidates in Bangladesh, Bhutan, Brazil, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, the Philippines, the United States, Timor-Leste, and Vietnam.
• Professional fluency in English and at least C1 English proficiency.
• At least 2 years of hands-on Swift and iOS development experience.
• Strong knowledge of Swift fundamentals, memory management, and automatic reference counting.
• Professional experience shipping or maintaining production mobile applications.
• A bachelor's degree in computer science or a closely related field.
• Significant experience using large language models for coding, debugging, and code review.
• Excellent English writing skills and the ability to explain complex technical ideas clearly.
• Experience reviewing app logic or mobile architecture.
• Previous AI data training or model evaluation experience is strongly preferred.
• Experience with SwiftUI, UIKit, Combine, and modern iOS architectures such as MVVM is highly preferred.

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

AI training work uses human reviews, examples, and feedback to help improve artificial intelligence systems. People with strong technical experience are needed to judge whether model outputs are correct, useful, and clearly written.