Certain terms and conditions of employment for this position, including the rate of pay, benefits, etc., are currently subject to negotiation with the appropriate union. Job
This position requires 1 day onsite per week, based on business needs, this may increase. 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. This 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. This role works closely with clinicians, data scientists, and IT teams to deliver solutions that are reliable, secure, and scalable.
Competitive applicants for this position are software, data, or machine learning engineers with 5+ years of experience building AI systems in production. They have strong skills in Python and SQL, and hands-on experience with MLOps, CI/CD, and cloud platforms (e.g., GCP, AWS, or Azure). Candidates should be comfortable developing and maintaining data pipelines, deploying machine learning or generative AI models, and building APIs or lightweight web applications, with the ability to work across the stack and deliver practical, user-facing solutions in a healthcare environment.
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.
UCSF Health IT provides clinical and informatics leadership to achieve the strategic priorities of UCSF Health, as enabled by technology. Health IT is a multidisciplinary team of clinicians and technology professionals that partners with clinical, business, and technology leaders throughout the organization, using information technology to improve the quality, safety, and value of care, and the patient and provider experience, for UCSF and its partner organizations.
Responsibilities % of time Essential Function (Yes/No ) Key Responsibilities (To be completed by Supervisor) 10 Y Applies advanced software concepts to plan, design, develop, modify, debug, deploy and evaluate highly complex software for functional areas. Analyzes existing highly complex software or works to formulate logic and devises algorithms for new highly complex software systems. Performs highly complex data analysis and tests / debugs highly complex software, working directly with management.
Initiates, analyzes, designs and applies highly complex data sources. Applies and enforces complex programming security practices. 10 Y Specifies, develops and executes complex test plans. Develops conversion and system implementation plans.
Performs or directs highly complex data modeling, performance and integration testing and builds interfaces. Determines source code control techniques and configuration management design and changes. 5 Y Prepares and approves or obtains approval for system and programming documentation. Initiates and oversees changes in development, maintenance and system standards.
Sets the technical requirements for complex software specifications. 5 Y Understands and applies industry practices, community standards and department policies and procedures in depth. May serve as technical lead for multiple software development projects of moderate to broad scope. May lead a team of software development professionals.
Enforces project plans. 15 Y Build and maintain data integration (with SQL databases or APIs) and data processing and transformation pipelines to support the development and implementation of AI/ML tools 15 Y Identify and build systems for implementation, monitoring, and maintenance of AI/ML tools using modern MLOps practices including CI/CD, model versioning, and cloud-native deployment. 5 Y Collaborate with data scientists and researchers to design and implement highly complex metrics and processes to automatically monitor AI/ML tools for safety, potential bias or drift, performance, and validity. 10 Design and develop APIs, services, or lightweight web applications to enable integration of AI/ML and generative AI capabilities into clinical and operational workflows. 15 Develop and deploy generative AI solutions (e.g., LLM-based systems), including prompt engineering, retrieval-augmented generation (RAG), and evaluation frameworks for unstructured data. 10 Design and implement highly complex real-time or near real-time data processing and inference systems to support AI/ML and generative AI applications.
Develop scalable, event-driven architectures and ensure reliable, low-latency integration of AI capabilities into production clinical and operational workflows 100% (To update total %, enter the amount of time in whole numbers (without the % symbol – e.g., 15, 20) then highlight the total sum (e.g., 1%) at the bottom of the column and press F9. The total sum should add up to 100%.) Required
Bachelor's degree in related area and / or equivalent experience / training. 5 years of experience in positions of increasing responsibility designing, implementing, and maintaining complex AI/ML applications. Experience with data analysis and machine learning tools such as Jupyter, Pandas, scikit-learn, Numpy/Scipy, PyTorch, etc. Demonstrated advanced knowledge of full software development lifecycle Advanced experience with Python; ability to write clean, efficient, and production-level Python code Advanced experience with SQL (e.g., SQLServer, PostgreSQL) Demonstrated 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) or integrating backend systems with user-facing applications 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 Demonstrated effective communication and interpersonal skills Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization Self-motivated and works independently and as part of a team.
Able to learn effectively and meet deadlines Demonstrated broad problem-solving skills Demonstrated ability to interface with management on a regular basis Excellent project leadership and management skills.
Master’s degree or PhD in Computer Science, Computer Engineering, or related area and/or equivalent experience/training. Epic Clarity or Clinical Data Model Familiar with data visualization tools (e.g., Tableau) Experience with Epic data structures
Full time · Day shift