Manager, Applied AI, Advanced Informatics

Discover Your Role Frame clinical and business informatics challenges into well-scoped AI/ML problem statements with clear success criteria Design and build ML pipelines (data ingestion, feature engineering, training, evaluation) alongside production engineering Run experiments, benchmarks, and ablation studies to validate model performance and guide modeling decisions Partner across clinical informatics, data engineering, and ML engineering to bring models into real workflows Track advances in foundation models, LLMs, and retrieval-augmented generation, and apply them to biomedical/health data Document research findings and contribute to internal reports, publications, or conference presentations Explain model behavior, limitations, and performance to technical and non-technical teams This Role Requires Bachelor’s in CS/ML/Data Science/Biomedical Informatics/Statistics or related; Master’s/Ph.D. strongly preferred with 4–6+ years applied AI/ML (Ph.D. research experience considered) Grounding in supervised, unsupervised, and self-supervised learning; deep neural networks; modern ML frameworks (PyTorch/TensorFlow or equivalent) Strong Python skills (scikit-learn, HuggingFace Transformers, pandas, NumPy) Experience designing/evaluating NLP or multimodal models, including LLM fine-tuning or prompt engineering Experiment tracking/versioning/reproducibility (MLflow, W&B, DVC, or similar) Familiarity with cloud ML (AWS SageMaker/GCP Vertex AI/Azure ML or equivalent) Experience with health/life sciences data (EHR/EMR, claims, clinical notes, genomic, imaging) Familiarity with medical terminologies/ontologies (SNOMED CT, ICD-10/11, LOINC, RxNorm, OMOP CDM) Published/open-source work in applied ML/NLP/computational biomedicine MLOps/CI/CD for ML or model observability in production Familiarity with federated learning, privacy-preserving ML, or regulated data use agreements #J-18808-Ljbffr Scorpion Therapeutics