ABOUT We are reimagining the phone. AI phones need to be proactive, intuitive, intelligent and low cost. This is a mission critical for rest of the world to adopt intelligence. There are over 5 billion people using everyday applications such as email, messaging, notes, tasks, and calendars, yet most are not AI-native. Our mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows, with minimal prompting.
RESPONSIBILITIES - Evaluate suitable open-weight and commercially available models for on-device execution. - Benchmark model performance on target mobile hardware. - Integrate models into Android applications and system services. - Optimize inference latency, memory consumption and power usage. - Evaluate quantization, compression and model distillation techniques. - Work with CPU, GPU and NPU acceleration. - Evaluate local model capabilities for different workflows. - Build hybrid local/cloud model routing mechanisms. - Identify which tasks can be handled locally and which require cloud inference. - Work with AI agent engineers to integrate local models into the agent runtime.
REQUIREMENTS - Strong ML systems or inference engineering experience. - Experience deploying and optimizing models. - Strong Python and C++ skills. - Understanding of neural network inference. - Experience with model quantization and performance optimization. - Understanding of hardware constraints and inference benchmarks. NICE TO HAVE - Experience with on-device LLMs. - Qualcomm QNN, MediaTek NeuroPilot or similar acceleration frameworks. - ONNX Runtime, LiteRT, TensorFlow Lite or ExecuTorch. - Android NDK. - Mobile or edge AI deployment. - Multimodal model optimization.
Job description provided by Bjak.
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