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  • London

  • 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.

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