AI Phone - On-device AI / ML Systems Engineer

The role

This person will evaluate and integrate models for on-device execution. They will optimize inference latency, memory consumption, and power usage on mobile hardware.

What you will do

• 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.

Required qualifications

• 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.

About the company

The mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows. They are reimagining the phone to be proactive, intuitive, intelligent and low cost.