Senior AI Research Engineer - Digital Health & Wearables

Samsung Research America (SRA); Mountain View (CA); On-site; USD 185,000 - 254,000; Full time

Job summary

Samsung Research America leads Digital Health initiatives and seeks a Senior AI Research Engineer with a PhD. You will develop AI/ML methods for physiological signals, digital biomarkers, and wearable health analytics, tackling large real-world datasets.

You will collaborate with hardware and software engineers to deploy models on wearable platforms, validate performance, and publish your findings while engaging with clinical and regulatory teams.

Qualifications

• PhD in AI, ML, Biomedical Engineering, CS, or related field.
• 3+ years of data analytics and health AI project experience.
• 3+ years of ML/DL experience with TensorFlow and PyTorch.
• Track record of publications in AI/ML venues or top journals.
• Experience with time-series data and biomedical wearables.

Responsibilities

• Research and develop novel AI/ML algorithms and foundation models for physiological signals and digital biomarkers.
• Design and implement deep learning and statistical models for multi-modal biosignals in real-time and batch settings.
• Scale algorithms to large multi-terabyte wearable datasets on cloud platforms.
• Collaborate with hardware and software engineers to enable on-device inference in wearables.
• Conduct feasibility studies, benchmark AI-driven features, and refine models for diverse populations.
• Coordinate with clinical/regulatory teams to ensure robustness and compliance.
• Stay current with digital health advances and publish findings in top venues.
• Generate patents and scientific papers for high-impact publications.

Skills

PhD in AI

Data analytics

ML/DL frameworks

Python

C++

TensorFlow

PyTorch

Publications

Education

PhD in AI/ML or related field

Tools

TensorFlow

PyTorch

Python

C++

Job description

Samsung Research America leads Digital Health initiatives and seeks a Senior AI Research Engineer with a PhD. You will develop AI/ML methods for physiological signals, digital biomarkers, and wearable health analytics, tackling large real-world datasets.

You will collaborate with hardware and software engineers to deploy models on wearable platforms, validate performance, and publish your findings while engaging with clinical and regulatory teams.