AI Engineer (AI Accelerator Program)

Job Summary The AI Engineer position requires 1 day onsite per week, with the possibility of increased onsite requirement based on business needs. UCSF Health is seeking a highly skilled AI Engineer to design, build, and deploy scalable AI‑driven applications that improve clinical operations, patient care, and health system efficiency. The role spans the full AI lifecycle, including data pipeline development, model training and evaluation, and deployment of machine learning and generative AI solutions on modern cloud platforms. The AI Engineer will translate emerging technologies, including large language models (LLMs), into production‑ready tools that integrate with healthcare systems. Responsibilities include building robust data pipelines, deploying machine learning and generative AI models, and developing APIs or web‑based applications that enable seamless use in clinical and operational workflows. The role works closely with clinicians, data scientists, and IT teams to deliver solutions that are reliable, secure, and scalable. Department Overview The Health AI team is part of the larger UCSF Health IT team and supports the development, implementation, and monitoring of artificial intelligence, machine learning, and other analytical tools, improving patient care, clinician experience, and health system operations. The team’s expertise spans data science, machine learning, software/data engineering, business, nursing informatics, and medical informatics. Key Responsibilities Apply advanced software concepts to design, develop, modify, debug, deploy, and evaluate highly complex AI/ML software. Build and maintain data integration and processing pipelines to support AI/ML tools. Identify, build, and deploy AI/ML monitoring and maintenance systems using MLOps practices (CI/CD, model versioning, cloud‑native deployment). Collaborate with data scientists and researchers to design and implement metrics and processes for automatic monitoring of AI/ML tools for safety, bias or drift, performance, and validity. Design and develop APIs, services, or lightweight web applications to integrate AI/ML and generative AI capabilities into clinical and operational workflows. Develop and deploy generative AI solutions (e.g., LLM‑based systems), including prompt engineering, retrieval‑augmented generation (RAG), and evaluation frameworks for unstructured data. Design and implement real‑time or near real‑time data processing and inference systems to support low‑latency AI/ML application integration in production workflows. Required Qualifications Bachelor’s degree in a related field or equivalent experience/training. 5+ years of experience in increasingly responsible roles designing, implementing, and maintaining complex AI/ML applications. Proficiency with data analysis and machine learning tools such as Jupyter, Pandas, scikit‑learn, NumPy/Scipy, PyTorch, etc. Advanced knowledge of the full software development lifecycle. Advanced experience writing clean, efficient, production‑level Python code. Advanced experience with SQL (e.g., SQL Server, PostgreSQL). Experience deploying, monitoring, and maintaining AI/ML models and pipelines. Experience designing and developing APIs or microservices to support AI/ML applications. Familiarity with web application development frameworks (e.g., React, JavaScript/TypeScript). Experience with large language models (LLMs), including prompt engineering, evaluation, and production deployment. Experience with real‑time or streaming data processing systems and low‑latency inference architectures. Strong communication and interpersonal skills. Ability to communicate technical information to both technical and non‑technical audiences. Self‑motivated, able to work independently and as part of a team. Strong problem‑solving skills. Experience interfacing with management and excellent project leadership/management skills. Preferred Qualifications Master’s degree or PhD in Computer Science, Computer Engineering, or a related area or equivalent experience/training. Experience with Epic Clarity or Clinical Data Model. Experience with Epic data structures. Familiarity with data visualization tools such as Tableau. Equal Employment Opportunity The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law. Salary Information The final salary and offer components are subject to additional approvals based on UC policy. Your placement within the salary range is dependent on factors including your work experience and internal equity within this position classification at UCSF. #J-18808-Ljbffr University of California - San Francisco