Android AI Mobile Engineer (Gemini Nano & Kotlin) - Q126

Job Title: Android AI Mobile Engineer (Gemini Nano & Kotlin)

Company: R2 Technologies

Location: Alpharetta, GA (Hybrid / Remote Options Available)

Employment Type: Full-Time / Contractual

About R2 Technologies: R2 Technologies is... (Same as above)

Job Summary: R2 Technologies is seeking an Android Mobile Engineer who specializes in the next generation of edge computing: On-Device AI. You will build mass-market, highly scalable Android applications that leverage Google's latest on-device models to offer smart replies, summarization, and offline NLP capabilities. Utilizing modern Kotlin, Jetpack Compose, and AI developer tools, you will craft fluid interfaces that seamlessly blend cloud AI with localized, on-device intelligence.

Key Responsibilities:

Architect and build modern Android applications using Kotlin, Coroutines, and Jetpack Compose.

Integrate Gemini Nano and ML Kit (LiteRT) to execute on-device AI tasks, ensuring low latency and strict data privacy for end-users.

Actively utilize AI-assisted development tools (Android Studio AI, Cursor, Copilot) to generate complex Compose UI layouts, write unit tests, and accelerate feature delivery.

Build secure, hybrid AI architectures that intelligently route heavy reasoning tasks to cloud LLMs while keeping sensitive context processing local to the device.

Optimize app performance, battery consumption, and thermal thresholds when running local machine learning inference.

Implement Clean Architecture and robust local storage solutions (Room, DataStore) to manage on-device semantic data.

Qualifications

• Bachelor degree in computer science or related field.

• 3 years of hands-on experience in native Android development using Kotlin.

• Strong proficiency in modern Android UI development using Jetpack Compose and Material Design 3.

• Familiarity with integrating ML Kit, TensorFlow Lite, or the Gemini Nano Android SDK.

• Proven experience or strong familiarity working alongside AI coding assistants to enhance productivity.

• Solid understanding of mobile lifecycle management, background processing, and battery optimization for intensive workloads.