8+ years of solid software development experience, with significant experience in mobile or cross-platform development.
Strong C++ development experience, with solid knowledge of C++14 and above.
Solid understanding of cross-platform mobile development and the ability to work effectively across both Android and iOS.
Familiarity with Android internals, including SurfaceFlinger and the Android graphics/rendering pipeline, with the ability to read and understand relevant source code.
Familiarity with iOS system architecture and native development concepts.
Strong understanding of Linux memory management and experience with POSIX APIs.
Good knowledge of computer networks and experience developing cross-platform applications using C++.
Good understanding of OpenGL/OpenGL ES principles and mobile graphics rendering.
Basic knowledge of ARM architecture and assembly is preferred.
Solid understanding of modern AI architectures, especially the Transformer architecture and core concepts such as attention mechanisms.
Familiarity with LLMs, AI agents, agentic workflows, and common AI application architectures.
Familiarity with on-device AI / edge AI, including model deployment, inference, quantization, and performance optimization on mobile devices.
Understanding of the trade-offs between model size, inference latency, memory consumption, power consumption, and accuracy on resource-constrained devices.
Bachelor's/Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience.
Good understanding of the mobile technology landscape, architectures, trends, and emerging technologies.
Experience developing shared C++ infrastructure or libraries used across Android and iOS.
Experience with AI model deployment or inference optimization on Android, iOS, or other edge devices.
Experience with model quantization, pruning, KV cache optimization, or other techniques for improving on-device AI performance.
Familiarity with AI inference frameworks or runtimes such as llama.cpp, ONNX Runtime, TensorFlow Lite, Core ML, or similar technologies.
Experience integrating LLMs or AI agents into mobile applications.
Familiarity with multimodal AI, speech AI, or other on-device AI technologies is a plus.
Experience contributing to popular mobile libraries or maintaining a widely used open-source project.
Knowledge of Android and iOS performance analysis and optimization techniques.
Strong problem-solving skills and the ability to work effectively across C++, Android, iOS, graphics, browser engines, JavaScript engines, and AI technologies.

Android Engineer (C

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