About this role
Design and validate applied AI/ML solutions for complex health data and clinical ground truth, build ML pipelines for data ingestion, feature engineering, training, and evaluation, and run experiments and benchmarks to guide modeling decisions. Collaborate with clinical informatics, data engineering, and ML engineering to bring models into informatics workflows and document research findings.
Skills for this role
Applied AIMachine LearningML pipelinesData ingestionFeature engineeringModel trainingModel evaluationExperimentationAblation studiesSupervised learningUnsupervised learningSelf-supervised learningDeep neural networksPyTorchTensorFlowPythonscikit-learnHuggingFace TransformerspandasNumPyNatural Language Processing (NLP)Multimodal modelsLLM fine-tuningPrompt engineeringExperiment trackingModel versioningReproducible researchMLflowW&BDVC