Proficiency with common ML and DL libraries (e.g., scikit-learn, NumPy, SciPy, PyTorch, TensorFlow/Keras), NLP/LLM libraries and APIs (e.g., Hugging Face libraries, LangChain or LlamaIndex, frontier model APIs, cloud and data platform APIs), and computer vision libraries (e.g., OpenCV, scikit-image, PIL, torchvision). This role requires deep expertise in machine learning and scientific leadership, with the ability to evaluate new technologies, incubate novel capabilities, and guide teams developing AI-enabled products in regulated healthcare environments.