AI/ML Engineer

Bring machine learning models to phones and wearables to provide real-time health insights, including offline. Optimize and deploy models for on-device inference, coordinate local and cloud processing, and collaborate with mobile, cloud, data science, and platform teams. Validate performance and outputs while supporting privacy, regulated development, and technical documentation.

Responsibilities

• Convert, optimize, and deploy models to i
• OS, Android, and wearable devices.
• Apply quantization, pruning, and distillation to meet latency, memory, and battery targets.
• Design on-device and cloud processing, including offline behavior, fallback, and synchronization.
• Build versioned processes for updating models on devices.
• Validate device model outputs against reference models and test across devices and operating systems.
• Collect on-device performance and quality metrics, integrate models with apps, and contribute to verification and documentation.

Required Skills

• Core MLTensor
• Flow Lite
• ONNX Runtime
• Model quantization
• Model pruning
• Model distillation
• Python
• Swift
• Kotlin
• C++