AI Engineer — Generative AI for Healthcare Ops

UCSF Health; San Francisco (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

UCSF Health is seeking a skilled AI Engineer to design, build, and deploy scalable AI‑driven applications that improve clinical operations and patient care. You will work across data pipelines, model training, evaluation, and cloud deployment to deliver reliable tools for workflows.

You will translate LLMs into production‑ready solutions, develop APIs, and implement robust monitoring for safety and bias. Collaboration with clinicians and IT teams is essential to success.

Qualifications

• 5 years of experience designing and maintaining AI/ML applications.
• Strong Python programming and production-grade code skills.
• Experience with data analysis tools (Jupyter, Pandas, NumPy).
• Hands-on ML model deployment and monitoring in production.
• Ability to design APIs or microservices for AI/ML use cases.
• Excellent communication and collaboration across teams.

Responsibilities

• Design, build, and deploy scalable AI-driven applications for clinical ops and care.
• Develop data pipelines, model training, evaluation, and cloud deployment.
• Create APIs or web apps enabling AI/ML in workflows.
• Implement MLOps practices: CI/CD, model versioning, monitoring.
• Collaborate with clinicians, data scientists, and IT teams.

Skills

Python

SQL

LLMs

MLOps

API development

Data analysis

Production-grade code

Communication

Team collaboration

Education

Bachelor's degree

Master’s degree or PhD (preferred)

Tools

Jupyter

Pandas

scikit-learn

NumPy/SciPy

PyTorch

Job description

UCSF Health is seeking a skilled AI Engineer to design, build, and deploy scalable AI‑driven applications that improve clinical operations and patient care. You will work across data pipelines, model training, evaluation, and cloud deployment to deliver reliable tools for workflows.

You will translate LLMs into production‑ready solutions, develop APIs, and implement robust monitoring for safety and bias. Collaboration with clinicians and IT teams is essential to success.