AI Phone - On-device AI / ML Systems Engineer

Bjak • Madison, MS

2d

About The Position

We are reimagining the phone to make AI proactive, intuitive, intelligent, and low cost, helping people around the world adopt intelligent technology. Although more than 5 billion people use everyday applications such as email, messaging, notes, tasks, and calendars, most are not AI-native. The mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination, and workflows with minimal prompting.

The engineer will evaluate models for on-device execution, benchmark and optimize them on mobile hardware, and integrate them into Android applications and system services. The role also involves assessing local model capabilities, building hybrid local/cloud routing, and collaborating 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 Haves

• Experience with on-device LLMs.
• Experience with Qualcomm QNN, MediaTek NeuroPilot, or similar acceleration frameworks.
• Experience with ONNX Runtime, LiteRT, TensorFlow Lite, or ExecuTorch.
• Experience with Android NDK.
• Mobile or edge AI deployment experience.
• Multimodal model optimization experience.

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.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed