Health Sensing ML Engineer

The Health Sensing team builds outstanding technologies to support our users in living their healthiest, the happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor SW & Prototyping team, we develop algorithms for a variety of health sensors, including PPG, accelerometer, ECG.

Description

In this role, you will be at the forefront of developing ML algorithms for health sensing applications and ensuring the efficient evaluation of these models to be in production at scale. You will interact closely with ML engineers, clinicians, software and hardware engineers. You will deliver solutions on time and with high quality standing up to the standards of a customer facing product.

Minimum Qualifications

BS in Computer Science, Engineering, Information Systems, or related technical field and a minimum of 3 years of equivalent experience
Proven experience in developing machine learning and deep learning models, preferably in the health domain
Proficiency in Python and ML frameworks e.g. PyTorch, Tensorflow
Experience with health data analysis, including time-series data, sensor data, and biomedical signal processing
Proven understanding of data preprocessing, feature extraction, and model evaluation techniques
Familiar with software development standard methods/teamworks
Sufficient SW skills to run large ML training jobs efficiently on a distributed backend with large volume of data

Preferred Qualifications

Interpersonal skills; comfortable in a collaborative and ground breaking research environments
MS or PhD or equivalent experience