Manager, Applied AI, Advanced Informatics
Core
Design and develop applied AI/ML solutions for health informatics use cases, translating clinical challenges into well-scoped problem statements and building reusable analytical capabilities.
Role type
Manager, Applied AI (Research-facing IC)
Builds
Applied AI/ML solutions, ML pipelines, and reusable analytical capabilities for health data systems
Domain
Health Informatics / Biomedical Data
Deliverable
production ML models
Required skills
Supervised/unsupervised/self-supervised learning, deep neural networks, Python, NLP/multimodal model design, LLM fine-tuning/prompt engineering, experiment tracking, cloud ML infrastructure
Preferred skills
Health/life sciences data (EHR, claims, genomic), medical terminologies/ontologies (SNOMED CT, ICD-10/11), MLOps/CI-CD, federated learning/privacy-preserving ML
Technologies
PyTorch, TensorFlow, scikit-learn, HuggingFace Transformers, pandas, NumPy, MLflow, W&B, DVC, AWS SageMaker, GCP Vertex AI, Azure ML
Responsibilities
Design and develop applied AI/ML solutions for health informatics use cases; Translate business and clinical informatics challenges into well-scoped AI/ML problem statements; Build and maintain ML pipelines including data ingestion, feature engineering, model training, and evaluation; Conduct experiments, benchmarking, and ablation studies to validate model performance; Partner with clinical informaticists, data engineers, and production AI/ML engineers to integrate models into informatics workflows; Stay current with advances in foundation models, LLMs, retrieval-augmented generation, and their application to biomedical and health data domains
Seniority
Manager, hands-on IC with strategic alignment