AI Phone - On-device AI / ML Systems Engineer

Bjak

United StatesRemote onlyFull time

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Location: United States
Work style: Remote only
Job type: Full time
Posted: Nov 4; 4 days ago

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About the company

Bjak

Computer software · 501 to 1,000 employees

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.

Bjak on LinkedIn

What you'll 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
Build hybrid local/cloud model routing mechanisms
Work with AI agent engineers to integrate local models into the agent runtime

What you need

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
Experience with on-device LLMs (preferred)
Qualcomm QNN, MediaTek NeuroPilot or similar acceleration frameworks (preferred)

Key skills

ML systemsinference engineeringPythonC++neural network inferencemodel quantizationperformance optimizationinference benchmarks

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Read the full posting here

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.