AI/ML Engineer

As AI/ML Engineer, you will bring machine learning models to mobile phones and wearables, so users receive real-time insights even without a network connection. You will own on-device inference, model optimization, and the logic that decides what runs locally and what runs in the cloud.

You will work closely with mobile and cloud engineers, data scientists, and the Data platform team, so strong collaboration and a high level of professionalism are required. This role shapes how the product works at the point of use.

What You'll Work On

• Convert, optimize, and deploy models to iOS, Android, and wearable devices using Core ML, TensorFlow Lite, ONNX Runtime, or similar.
• Apply quantization, pruning, and distillation to meet latency, memory, and battery targets without losing clinical accuracy.
• Design the on-device and cloud split, including offline behavior, fallback, and synchronization of results.
• Build a safe, versioned process for updating models on devices, in partnership with the ML platform team.
• Validate that on-device model outputs match reference models and build tests across device types and OS versions.
• Collect on-device performance and quality metrics while respecting user privacy.
• Partner with mobile engineers to integrate models into the app and sensor experience.
• Contribute to design reviews, verification activities, and technical documentation in compliance with government and corporate regulations.
• Proactively identify problems or areas for improvement and resolve issues.

Qualifications

• Bachelor's or Master's degree in Computer Science, or a related field.
• 6+ years of software or ML engineering experience, including 3+ years deploying ML models on mobile or embedded devices.
• Hands-on experience with Core ML, TensorFlow Lite, ONNX Runtime, or equivalent edge inference frameworks.
• Proven experience with model optimization techniques such as quantization and pruning.
• Proficiency in Python plus at least one of Swift, Kotlin, or C++.
• Understanding of mobile performance constraints: battery, memory, latency, and background execution.

Preferred Qualifications

• Experience in a regulated industry, ideally medical devices or SaMD, including software verification and validation.
• Experience with wearable, Bluetooth, or sensor-connected devices.
• Experience running small language models on device.
• Familiarity with IEC 62304 and privacy-preserving techniques such as federated learning.