Machine Learning Engineer

4 weeks ago


San Francisco, California, United States University of California, San Francisco Full time
Job Summary

The University of California, San Francisco (UCSF) is seeking a highly skilled Machine Learning Engineer to lead the development, implementation, and maintenance of data pipelines and infrastructure to support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools at UCSF Health. This role primarily involves managing and optimizing the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure that supports the development and deployment of AI/ML tools, including large language models (LLMs) in the EHR.

Key Responsibilities
  • Implementing new data integrations and enhancing HIPAC's ETL functionalities
  • Productionizing AI/ML tools developed by UCSF data scientists/researchers
  • Designing and implementing metrics to continuously monitor AI/ML tools deployed at UCSF Health
Requirements
  • 2+ years of experience in implementing and maintaining AI/ML pipelines
  • Proficiency in MLOps, Python, SQL, and CI/CD
  • Deep understanding of Epic data models (Clarity and Caboodle)
Preferred Qualifications
  • Master's degree or PhD in Computer Science, Computer Engineering, or related area
  • Epic Clarity or Clinical Data Model certification
  • Experience with large language models and other generative AI technologies
About UCSF

UCSF Health is a world-renowned institution dedicated to providing the highest quality patient care, advanced technology, and pioneering research. Our team is committed to delivering the best care possible while fostering a collaborative and inclusive work environment.



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