Staff AI Applied Scientist

Join to apply for the Staff AI Applied Scientist role at Verily Who We Are Verily is a subsidiary of Alphabet that is using a data‑driven approach to change the way people manage their health and the way healthcare is delivered. Launched from Google X in 2015, our purpose is to bring the promise of precision health to everyone, every day. We are focused on generating and activating data from a variety of sources, including clinical, social, behavioral and the real world, to arrive at the best solutions for a person based on a comprehensive view of the evidence. Our unique expertise and capabilities in technology, data science and healthcare enable the entire healthcare ecosystem to drive better health outcomes. Description As an AI and Data Scientist at Verily, you will be supporting our core mission to build advanced data and AI capabilities for Verily’s portfolio of products. You will help drive innovation in data‑driven healthcare applications by developing and deploying sophisticated models. Your work will involve utilizing cutting‑edge techniques to analyze complex datasets, uncover patterns, and build robust, data‑driven solutions that address healthcare challenges. You will collaborate with a diverse cross‑functional team to build reusable and scalable tools that unlock information from structured and unstructured clinical data. Responsibilities Drive Verily’s AI and data strategy, shaping initiatives that advance our mission to transform healthcare through data‑driven innovation. Lead high‑impact data science programs, developing and implementing advanced algorithms to address complex healthcare challenges. Design and scale robust data architectures and pipelines that ensure quality, integrity, and accessibility of data across the organization. Develop and deploy sophisticated machine learning models to generate actionable insights, forecast trends, and inform strategic decisions. Partner with and mentor cross‑functional teams, translating complex findings into clear, actionable narratives and fostering a culture of technical excellence. Minimum Qualifications Advanced degree in a quantitative discipline (e.g., computer science, statistics, applied mathematics, biomedical informatics, biomedical engineering) or equivalent practical experience. 7+ years experience applying advanced machine learning and AI techniques (e.g., supervised and unsupervised methods, LLMs, NLP) to clinical data in digital health applications. Direct experience working with and curating real‑world data, such as EHR, including a deep understanding of the complexities of structured and unstructured clinical data. Direct experience working with Large Language Models (LLMs) and familiarity with prompt optimization technologies. Strong proficiency in Python. Preferred Qualifications Ph.D. in a quantitative discipline with an additional focus on AI and machine learning. Deep experience with LLM models, including prompting, fine‑tuning, and retrieval‑augmented generation (RAG). Experience with software engineering practices and a track record of developing and deploying production software. Deep experience with clinical data, including medical terminologies and ontologies. Experience developing transformer‑based deep learning algorithms using TensorFlow or PyTorch, with knowledge of the latest architectures. Creative and methodical problem‑solving skills with an ability to understand needs, identify options, form hypotheses, and make informed decisions. Ability to work cross‑functionally and lead projects, with a tolerance for ambiguity. This role is eligible for Verily‑sponsored immigration support. Verily Life Sciences LLC is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you’d like more information on your EEO rights under the law, please click here. If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form. #J-18808-Ljbffr