Ucsf Medical Center - San Francisco, CA
posted about 2 months ago
The Machine Learning / Data Engineer at UCSF Health will play a pivotal role in the development, implementation, and maintenance of data pipelines and infrastructure that support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools. This position is integral to the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure designed to facilitate the development and deployment of AI/ML tools, including large language models (LLMs) within the Electronic Health Record (EHR) system. The engineer will be responsible for managing and optimizing data and monitoring pipelines, implementing new data integrations, enhancing ETL functionalities, and productionizing AI/ML tools developed by UCSF data scientists and researchers. Additionally, the role involves designing and implementing metrics to continuously monitor the performance of AI/ML tools deployed at UCSF Health. Candidates for this position should have a strong background in software, machine learning, or data engineering, with at least two years of experience in implementing and maintaining AI/ML pipelines. Proficiency in MLOps, Python, SQL, and CI/CD is essential, along with a deep understanding of Epic data models (Clarity and Caboodle). Successful candidates will either possess or be able to obtain Epic Clinical/Clarity data model certification shortly after onboarding. The position offers a competitive salary range of $125,500 - $188,300, with placement dependent on experience and internal equity within the classification at UCSF. The Health AI team is part of the larger UCSF Health IT team, which focuses on improving patient care, clinician experience, and health system operations through advanced technology and analytics.