We’re always seeking talented AI engineers and post-doctoral researchers to join our research team. If any of the positions below interest you, please reach out! Females and underrepresented groups are particularly encouraged to apply.
Senior AI Engineer for the PROSPECT Team
Our team serves as the data science arm of the PROSPECT lab, which is the digital innovation team at Zuckerberg San Francisco General Hospital. The mission of PROSPECT is to improve health outcomes and equity in vulnerable and underserved populations through the application of novel technologies and digital tools. Our team is composed of experts in machine learning, artificial intelligence, data science, informatics, building and analytics within the electronic health record, health equity and social determinants of health. We’re looking for a senior AI engineer to join our team, who will help architect, implement, and scale AI technologies at the hospital. As part of this role, you’ll have opportunities to support or even conduct AI research as well.
Primary Responsibilities
- Develop and deploy production-grade AI applications that integrate directly into the EHR system
- Build and maintain PHI-compliant data pipelines that process high volumes of clinical notes and multi-modal Electronic Health Record (EHR) data
- Architect and implement cloud-based infrastructure (AWS or similar platforms) for deploying scalable AI applications
- Design and maintain a standardized database for EHR data to support ML/AI applications across the team
- Create robust infrastructure and tooling to enable and accelerate AI research efforts for the broader team
- Develop ETL pipelines that extract, process, and analyze large-scale multi-modal EHR data
- Ensure all systems meet HIPAA compliance and healthcare security standards
- Collaborate closely with clinicians, informaticists, and interdisciplinary team members
- Prepare and submit research manuscripts to ML/AI conferences and/or clinical AI journals
- Design and implement open-source software packages for the research and clinical communities
Qualifications
The position requires an MS or PhD in computer science, data science, or a related field and/or equivalent working experience. We are looking for someone who:
- Has strong software engineering skills with experience building production systems
- Has experience with cloud platforms (AWS, Azure, or GCP) and containerization (e.g., Docker)
- Is proficient in designing databases, building scalable data pipelines, and processing large-scale datasets
- Can work independently and take ownership of complex technical projects
- Has experience with EHR systems and healthcare data integration (strongly preferred)
- Has experience with natural language processing and processing clinical notes (strongly preferred)
- Has interest in methodological development and independent research (strongly preferred)
Postdoctoral Fellow in developing clinical AI monitoring systems
This project aims to develop a suite of statistical and computational methods that hospitals can use to monitor changes in performance of clinical AI algorithms and, subsequently, diagnose the root cause and update the model. The team is led by Drs. Feng and Suchi Saria. Other team members include faculty across UCSF, JHU, and Northwell with expertise in ML/AI/statistics and medicine, including Fan Xia, Julian Hong, Lucas Zier, Arjun Sondhi, and more!
Primary responsibilities:
- Develop tools for monitoring, diagnosing, and updating ML/AI systems in real-world clinical settings with rigorous statistical guarantees. See example papers from our group here, here, here, here, and here.
- Design and implement robust, scalable software libraries and data pipelines
- Collaborate with deployment teams to ensure developed tools work well in real-world settings
- Prepare and submit research manuscripts and technical reports
Qualifications:
The post-doctoral researcher position requires at least a PhD degree in computer science, (bio)statistics, data science, or related fields. We are looking for someone who:
- has experience in methodological development and can perform independent research, with a strong and relevant publication record
- (preferably) has experience in at least one of these fields: sequential monitoring, multiple hypothesis testing, machine learning, causal inference, post-prediction inference
- is comfortable working with large datasets as well as data from different modalities (tabular, imaging, text)
- is able to work collaboratively with a team
Applying
If you are interested in either position, please submit the following materials to :
- A cover letter
- A CV summarizing your education and work experience so far
- The names and email addresses of three references
- A github repo of yours that you are most proud of
- One representative publication
Screening of applicants will begin immediately and will continue as needed throughout the recruitment period.
Updated 01/04/2026
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.