Manager, Applied AI, Advanced Informatics

What you'll do

• Translate clinical and business informatics challenges into well-scoped AI/ML problem statements with clear success criteria.
• Design and build end-to-end ML pipelines including data ingestion, feature engineering, training, and evaluation.
• Conduct experiments, benchmarks, and ablation studies to validate model performance and guide modeling decisions.
• Integrate developed models into real-world clinical informatics workflows in collaboration with engineering teams.
• Track and apply advancements in foundation models, LLMs, and retrieval-augmented generation to biomedical data.
• Document research findings for internal reports, publications, or conference presentations.
• Communicate model behavior, limitations, and performance metrics to both technical and non-technical stakeholders.

What we're looking for

• Bachelor's degree in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Statistics, or a related field.
• Master's or Ph.D. preferred with 4–6 years of progressive experience in applied AI/ML.
• Proficiency in supervised, unsupervised, and self-supervised learning using PyTorch or TensorFlow.
• Strong Python skills across the scientific ML stack including scikit-learn, HuggingFace Transformers, pandas, and NumPy.
• Experience designing and evaluating NLP or multimodal models, including LLM fine-tuning and prompt engineering.
• Familiarity with cloud-based ML infrastructure such as AWS SageMaker, GCP Vertex AI, or Azure ML.
• Experience working with health or life sciences data and medical terminologies like SNOMED CT, ICD-10/11, and OMOP CDM.
• Experience with MLOps, CI/CD for ML, or model observability in production environments.