We are partnering with a technology company building AI-enabled smart devices and are looking for an engineer who can bring machine learning directly onto Android-based hardware.

This role focuses on running AI models on-device rather than in the cloud — working close to the Android system layer to deliver real-time intelligence for next-generation IoT products.

If you enjoy solving performance challenges, optimizing ML inference, and working with Android internals, this could be an excellent fit.

What you'll be working on

• Deploying and optimizing machine learning models on Android devices
• Building AI features that process video, audio, and sensor data in real time
• Improving performance, power efficiency, and stability for ML workloads on embedded devices
• Integrating models from data science teams into production Android systems
• Troubleshooting system-level issues such as memory bottlenecks, crashes, or deadlocks
• Contributing to the core platform powering AI-driven IoT products

What they're looking for

• 3+ years of experience developing software for Android platforms
• Experience implementing or integrating machine learning models on mobile or edge devices
• Strong programming experience in Java, Kotlin, or C/C++
• Solid understanding of Android system internals (memory, scheduling, drivers, kernel interactions)
• Experience diagnosing performance and system stability issues
• Familiarity with TensorFlow Lite, PyTorch Mobile, or other mobile ML frameworks

Useful additional experience

• Video or audio processing on Android
• Computer vision or speech recognition models
• Running LLM inference on edge devices
• Model optimization techniques such as quantization, distillation, or conversion for mobile deployment