Machine Learning Engineer
About The Position
The Machine Learning Engineer will lead the development, implementation, and maintenance of data pipelines and infrastructure that support deployment and continuous monitoring of machine learning and generative AI tools within UCSF’s APeX Enabled Research (AER) team. The role works closely with UCSF technical teams, researchers, and data scientists to create customized research solutions. It primarily manages and optimizes data and monitoring pipelines for the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure supporting AI/ML tools, including large language models, in the electronic health record. Key work includes implementing data integrations, enhancing HIPAC’s ETL capabilities, productionizing AI/ML tools developed by UCSF researchers, and designing metrics and processes for ongoing monitoring of tools deployed at UCSF Health. The position also supports AER’s broader research services, which include project consultation, grant support, budget estimates, implementation, and support for research projects involving EHR-based interventions, clinical trials, digital tools, and scalable research infrastructure. This is a grant-funded, 18-month Limited Appointment. The position is flexible, with two days on-site, and requires availability for on-site lab meetings that may occur weekly or bi-weekly depending on departmental needs. Certain employment terms, including pay and benefits, are subject to negotiation with the appropriate union.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, or a related area, and/or equivalent experience or training.
- Six 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, and PyTorch.
- Advanced knowledge of the full software development lifecycle.
- Advanced Python experience, including writing clean, efficient, production-level code.
- Advanced SQL experience, such as SQL Server or PostgreSQL.
- Experience deploying, monitoring, and maintaining AI/ML models and pipelines.
- Advanced experience with database systems, data warehousing solutions, and ETL pipelines.
- Advanced experience designing, building, or maintaining data infrastructure for efficient ML model training and inference.
- Experience with MLOps, DevOps, and CI/CD toolsets.
- Experience developing complex automated testing.
- Experience with cloud-based architecture on platforms such as AWS, GCP, or Azure.
- Effective communication and interpersonal skills, including the ability to communicate technical information to technical and non-technical audiences at different organizational levels.
- Ability to work independently and collaboratively, learn effectively, meet deadlines, and solve problems broadly.
- Ability to interface regularly with management.
- Strong project leadership and management skills.
Nice To Haves
- Master’s degree or PhD in Computer Science, Computer Engineering, or a related area, and/or equivalent experience or training.
- Experience with large language models and other generative AI technologies, especially deployment of GenAI-based tools in production.
- Familiarity with data visualization tools such as Tableau.
- Experience with Epic data structures.
- Epic Clarity Certification.
- Cloud development certifications.
Responsibilities
- Plan, design, develop, modify, debug, deploy, and evaluate complex software; analyze existing systems, devise algorithms, conduct data analysis, and apply programming security practices.
- Develop and execute test plans, implementation plans, data models, performance and integration tests, and interfaces; determine source-code control and configuration-management approaches.
- Prepare or obtain approval for system and programming documentation, oversee changes to development and maintenance standards, and define technical requirements for software specifications.
- Apply industry practices, standards, and department policies; potentially serve as technical lead for software projects and lead development professionals.
- Build and maintain data integrations with SQL databases or APIs, along with data processing and transformation pipelines for AI/ML tools.
- Identify and build systems for implementation, monitoring, and maintenance of AI/ML tools; collaborate with researchers and developers to productionize and maintain tools in the Health System.
- Collaborate with data scientists and researchers to design and implement metrics and automated processes to monitor AI/ML tools for safety, potential bias or drift, performance, and validity.
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What This Job Offers
Career Level
Senior
