Android Engineer (Kotlin and Java) Code Review

You will review AI-generated Android code, architecture choices, and technical explanations. You will also write reference implementations, create prompts and model answers, and compare responses for technical quality.

• Review Android code and architecture decisions involving Jetpack Compose, Views, lifecycle behavior, networking, persistence, memory, and performance.
• Evaluate concurrency, coroutines, Flow, threading, cancellation, race conditions, and application-not-responding risks.
• Rate AI responses for correctness, reasoning quality, security, performance, clarity, maintainability, and prompt adherence.
• Write clear reference implementations and step-by-step explanations for complex Android problems.
• Create Android prompts and reference answers to support AI training.
• Identify inaccurate, unsafe, or subtly flawed Android recommendations.
• Check technical content across testing, dependency injection, modularization, CI/CD, and release workflows.

This is an intermediate-level, remote contractor role for Android engineers who want to apply their technical judgment to AI evaluation and training work.

• Pay: $35 to $110 per hour.
• Time: 20+ hours per week.
• Work arrangement: Remote, part-time contract work.
• Location: Open to candidates in Bangladesh, Bhutan, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, the Philippines, the United States, Timor-Leste, and Vietnam.
• Language: Clear written English is required.
• Experience: Strong production Android experience with Kotlin is required; Java experience is preferred.
• Android knowledge: App lifecycle, Activities and Fragments, state restoration, background execution limits, Jetpack Compose or Views, recomposition, state hoisting, and UI performance.
• Concurrency: Coroutines, Flow, threading practices, cancellation, race-condition prevention, and avoiding application-not-responding issues.
• Architecture and data: MVVM, Clean Architecture, dependency injection, modularization, Retrofit, OkHttp, Room, SQLite, and DataStore.
• Quality and security: Unit, instrumentation, and UI testing; CI/CD and release workflows; secure storage, authentication flows, certificate pinning, and privacy permissions.
• Helpful background: AI data training, annotation, AI-generated technical content evaluation, Android code review, or debugging workflows.

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

AI training is the human work behind systems that learn from examples. In this role, your Android expertise helps evaluate and improve model-generated code, explanations, and technical decisions, which is why strong specialist experience matters.