The posting
Job Description
This is a grant funded, 18 month, Limited Appointment position.
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.
This position is considered flexible, 2 days on-site, and must be available for lab on-site meetings that may happen once per week or bi-weekly, based on needs of the department.
The Machine Learning and Data engineer role will lead the development, implementation, and maintenance of data pipelines and infrastructure to support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools within UCSF’s APeX Enabled Research (AER) team. Most projects will be in partnership with other UCSF technical teams and involve highly customized research solutions. Communication skills and inventive technical solutioning are crucial.
The AER team provides a large array of services to the UCSF Research community, including project consultation, grant support, budget estimations, and project implementation and support. Project examples include:
- Development of EHR-based interventions via clinical trials embedded within healthcare delivery systems to generate scientific evidence while delivering healthcare. Enabling UCSF researchers with algorithms, digital tools and / or clinical interventions with strong evidence of feasibility and acceptability. Develop technical approaches and budgets in order to implement these tools within the electronic medical record. Supporting the development of scalable, low cost infrastructure to enable ongoing research.
This role primarily involves managing and optimizing the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure that supports the development and deployment of AI/ML tools, including large language models (LLMs) in the EHR. Specifically, the ML/data engineer will work on implementing new data integrations, enhancing HIPAC’s ETL functionalities, productionizing AI/ML tools developed by UCSF data scientists/researchers, and designing and implementing metrics to continuously monitor AI/ML tools deployed at UCSF Health.
Competitive applicants for this position are software, machine learning, or data engineers with 6+ years of experience in implementing and maintaining AI/ML pipelines. Proficiency in MLOps, Python, SQL, and CI/CD is required. This role also requires a deep understanding of Epic data models (Clarity and Caboodle). Successful candidates either have or are able to obtain Epic Clinical/Clarity data model certification shortly after onboarding.
Department Overview
The University of California, San Francisco (UCSF) Department of Information Technology Academic Research Systems (ARS) group is chartered to provide data services and infrastructure that support the UCSF Research Community’s computing and analytic requirements through centralized informatics services in the areas of Data, Tools, Secure Compute Environments, and Consulting Services.
Responsibilities
%
of time
Essential Function (Yes/No)
Key Responsibilities
(To be completed by Supervisor)
10%
Yes
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%
Yes
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%
Yes
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%
Yes
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.
25%
Yes
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
20%
Yes
Identify and build systems for implementation, monitoring, and maintenance of AI/ML tools. Collaborate with researchers and developers to productionize and maintain AI/ML tools in the Health System.
25%
Yes
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.
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%.)
Qualifications
REQUIRED QUALIFICATIONS
- Bachelor's degree in Computer Science, Computer Engineering, or related area and / or equivalent experience / training.
- 6 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
- Advanced experience in database systems, data warehousing solutions, and understanding of ETL pipelines
- Advanced experience in designing, building, or maintaining data infrastructure for efficient ML model training and inference.
- Demonstrated experience working with MLOps, DevOps, and CI/CD pipeline toolsets
- Experience in developing complex, automated testing
- Experience with cloud-based architecture in platforms such as AWS, GCP, Azure
- 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.
PREFERRED QUALIFICATIONS
- Master’s Degree or PhD in Computer Science, Computer Engineering, or related area and / or equivalent experience / training.
- Experience with large language models and other generative AI technologies, especially supporting the deployment of GenAI-based tools in a production environment
- Familiar with data visualization tools (e.g., Tableau)
- Experience with Epic data structures
- Epic Clarity Certification
- Cloud Development certifications
About Us
About UCSF
The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences. We bring together the world’s leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells.
Pride Values
UCSF is a diverse community made of people with many skills and talents. We seek candidates whose work experience or community service has prepared them to contribute to our commitment to professionalism, respect, integrity, diversity and excellence – also known as our PRIDE values.
In addition to our PRIDE values, UCSF is committed to equity – both in how we deliver care as well as our workforce. We are committed to building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for the provision of culturally competent education, discovery, and patient care. Additional information about UCSF is available here.
Join us to find a rewarding career contributing to improving healthcare worldwide.
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 a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement.
To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html
