University of California, San Francisco
1 week ago
Machine Learning and Data Engineer for Healthcare AI/ML Infrastructure at UCSF University of California, San Francisco in United States
Degree Level
not provided
Field of study
Computer Science
Funding
This is a grant-funded, 18-month limited appointment full-time staff position. Compensation, benefits, and related employment terms are subject to negotiation with the appropriate union. No student stipend, tuition funding, or scholarship is specified.
Country
United States
University
University of California, San Francisco
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About this position
The University of California, San Francisco (UCSF) is hiring a full-time Machine Learning Engineer for its Academic Research Systems team and APeX Enabled Research (AER) group in San Francisco, United States. This is a grant-funded, 18-month limited appointment with a flexible workplace arrangement requiring approximately two days on site and periodic laboratory meetings.
The role focuses on machine learning, data engineering, MLOps, generative artificial intelligence, and healthcare informatics. The successful candidate will lead the development, implementation, and maintenance of data pipelines and infrastructure supporting the deployment and continuous monitoring of AI/ML tools, including large language models, within UCSF Health's electronic health record environment.
Responsibilities include implementing data integrations, improving ETL functionality, productionizing AI/ML tools developed by UCSF researchers, and designing metrics to monitor deployed models. The position works with HIPAC, UCSF's Health IT Platform for Advanced Computing, and supports research involving clinical trials, EHR-based interventions, digital health tools, scalable infrastructure, and evidence-generation in healthcare.
Applicants should hold a bachelor's degree in Computer Science, Computer Engineering, or a related field, or have equivalent training and experience, and must have at least six years of relevant professional experience. Required technical skills include production-level Python, advanced SQL, machine learning libraries, database and data warehousing systems, cloud architecture, CI/CD, DevOps, MLOps, automated testing, and AI/ML deployment and monitoring. Familiarity with Epic Clarity and Caboodle data models is important; candidates must have or be able to obtain Epic Clinical/Clarity certification after onboarding.
A master's degree or PhD, experience deploying generative AI and large language models in production, Epic data experience, Tableau familiarity, Epic Clarity certification, and cloud development certifications are preferred. The position is not a PhD, postdoctoral, or master's study opening and does not advertise scholarship or tuition funding.
Funding details
This is a grant-funded, 18-month limited appointment full-time staff position. Compensation, benefits, and related employment terms are subject to negotiation with the appropriate union. No student stipend, tuition funding, or scholarship is specified.
What's required
A bachelor's degree in Computer Science, Computer Engineering, or a related area, or equivalent experience and training, is required, along with at least six years of progressively responsible experience designing, implementing, and maintaining complex AI/ML applications. Candidates need advanced Python and SQL skills; experience with Jupyter, Pandas, scikit-learn, NumPy/SciPy, PyTorch, database systems, data warehousing, ETL pipelines, MLOps, DevOps, CI/CD, automated testing, cloud platforms such as AWS, GCP, or Azure, and deployment, monitoring, and maintenance of AI/ML models. Effective communication, problem-solving, project leadership, independence, teamwork, and the ability to communicate with technical and non-technical personnel are required. Preferred qualifications include a master's degree or PhD, experience with large language models and generative AI in production, data visualization tools such as Tableau, Epic data structures, Epic Clarity certification, and cloud development certifications.
How to apply
Apply through the UCSF Careers job portal using Job ID 10841 or the direct posting link. Review the qualifications and submit the requested application materials through the portal.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.