WHO we’re looking for:

We are looking for a Machine Learning Engineer (Health) with solid ML/AI technology background and digital health-related research project experiences in health data analytics, physiological signal process, and multi-modality mobile sensing development. By leveraging smartphones, wearables, and hearables in the health/wellness domain, your work will significantly benefit real-world consumers, patients, the elderly, physicians, and caregivers.

Our unique advantage in the consumer electronics market and growing focus on digital health will provide you with unprecedented large data sets and healthcare analytics challenges.

The Digital Health Team collaborates with top hospitals, healthcare-industry partners, and universities to transform how healthcare is delivered and good health sustained. Using design thinking to address some of healthcare’s toughest challenges, from improving care and producing better outcomes, to reducing costs and expanding access.

Focusing on wearable, mobile, and cloud-based form factors, our multi-disciplinary team develops innovative technologies that we then turn into groundbreaking commercial products to support clinicians, patients, and consumers. Using advanced sensor technology to capture physiologic responses and make use of our AI/ML framework to build algorithms that detect and trigger alerts for specific health conditions. Employing data analytics to supplement clinical care and facilitate remote patient monitoring, thereby helping patients make behavioral changes that improve their health and daily lives.

Our portfolio of digital health solutions are important tools in helping clinicians and their patients monitor and manage serious health conditions, such as cardiovascular disease, pulmonary disease, and cancer; as well as chronic illnesses including mental health, diabetes, hypertension, depression, sleep disorders, and obesity. Our work encompasses the entire range of processes, from ideating, developing, and incubating; to designing and delivering market-ready products; to supporting and evolving currently released products.

Role and Responsibilities:

Work with an agile team to innovate and develop disruptive digital health services and solutions.
Develop innovative algorithms and biomarkers based on signal from an array of sensors and devices, data collected both in lab and field settings, and health data from consumers, and healthcare providers.
Develop generalizable data analysis pipeline including data segmentation, alignment, cleaning, annotation, and pre-processing for biomarker prediction.
Prepare proof-of-concept, demo/prototypes, and execute studies with mobile sensors.
Client-server pipeline integration for PoC and demo app.
Digital biomarker algorithm optimization for on-device (e.g., watch, buds) PoC.
Develop server-side data processing framework to run the data analysis pipelines on big datasets

Required Experience and Education:

MS or PhD in computer science / computer engineering / biomedical engineering / electrical engineering / Data Science / Machine Learning background with 2-3 years of work experience (Bachelor's Degree required).
Solid coding skills with prototyping experience for projects focused on signal processing and machine learning.
Experience in signal processing and time-series feature engineering on health datasets.
Strong knowledge of signal processing and machine learning packages in Python.
Prior experience with deep learning frameworks including TensorFlow and PyTorch.
Experience with Machine Learning Engineering on AWS.

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