On-Device AI/ML Engineer for Mobile & Wearables

Thornton Tomasetti; Alameda (CA); On-site; USD 100,000 - 200,000; Full time

Benefits offered by this job

Career development

Health plan

Retirement plan

Tuition reimbursement

Diversity recognition

Job summary

Abbott in Alameda, CA is seeking an AI/ML Engineer to bring machine learning models to mobile devices and wearables. You will own on-device inference, model optimization, and decide what runs locally versus in the cloud, partnering with mobile and cloud engineers and data scientists.

Qualifications include a Bachelor's or Master's in CS, 6+ years in software/ML, and experience with Core ML, TensorFlow Lite, ONNX Runtime, and Python plus Swift/Kotlin/C++.

Qualifications

• Bachelor's or Master’s degree in Computer Science or 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.

Responsibilities

• Convert, optimize, and deploy models to iOS, Android, and wearable devices.
• Apply quantization, pruning, and distillation to meet latency, memory, and battery targets.
• Design the on-device and cloud split, including offline behavior and synchronization of results.
• Build a safe, versioned process for updating models on devices, in partnership with the ML platform team.
• Validate on-device model outputs and build tests across device types and OS versions.
• Collect on-device performance and quality metrics while respecting user privacy.

Skills

Python

Swift/Kotlin/C++

Edge ML deployment

Model optimization

On-device inference

Education

Bachelor's or Master’s degree in Computer Science or related field

Tools

Core ML

TensorFlow Lite

ONNX Runtime

Job description

Abbott in Alameda, CA is seeking an AI/ML Engineer to bring machine learning models to mobile devices and wearables. You will own on-device inference, model optimization, and decide what runs locally versus in the cloud, partnering with mobile and cloud engineers and data scientists.

Qualifications include a Bachelor's or Master's in CS, 6+ years in software/ML, and experience with Core ML, TensorFlow Lite, ONNX Runtime, and Python plus Swift/Kotlin/C++.