Senior Machine Learning Engineer

What you will do

Model development. Design, train, and evaluate clinical prediction models, with feature engineering across physiological time series and structured EHR context.
Labels and ground truth. Define what you are actually predicting with clinical teams, build adjudication workflows, and understand the noise in your targets.
Evaluation and testing infrastructure. Build the eval harnesses, backtesting, and regression suites that let us ship new model versions and new configurations with confidence, including how flagging behaves and whether explanations hold up.
Clinical evaluation. Sensitivity, specificity, lead time, and alert burden as the care team experiences them. Threshold selection is a clinical decision as much as a statistical one.

Model development. Design, train, and evaluate clinical prediction models, with feature engineering across physiological time series and structured EHR context.
Labels and ground truth. Define what you are actually predicting with clinical teams, build adjudication workflows, and understand the noise in your targets.
Evaluation and testing infrastructure. Build the eval harnesses, backtesting, and regression suites that let us ship new model versions and new configurations with confidence, including how flagging behaves and whether explanations hold up.
Clinical evaluation. Sensitivity, specificity, lead time, and alert burden as the care team experiences them. Threshold selection is a clinical decision as much as a statistical one.