Machine Learning Engineer

UCSF Campus BU is hiring a grant funded Machine Learning Engineer to support the APeX Enabled Research (AER) team. This 18 month Limited Appointment role focuses on building and maintaining data pipelines and infrastructure that deploy and continuously monitor ML and generative AI tools across UCSF Health.

Role Summary

In this position, you will lead development, implementation, and maintenance of data pipelines and infrastructure for deploying and continuously monitoring machine learning and generative AI tools. The work supports the UCSF Health IT Platform for Advanced Computing (HIPAC) and includes productionizing AI/ML tools for use within the electronic health record (EHR).

Key Responsibilities

• Lead development, implementation, and maintenance of data pipelines and infrastructure supporting deployment and continuous monitoring of Machine Learning and generative Artificial Intelligence tools within UCSF’s APeX Enabled Research (AER) team.
• Manage and optimize HIPAC data and monitoring pipelines.
• Implement new data integrations.
• Enhance HIPAC’s ETL functionalities.
• Productionize AI/ML tools developed by UCSF data scientists and researchers.
• Design and implement metrics to continuously monitor deployed AI/ML tools at UCSF Health.
• Support ongoing efforts involving data integrations, HIPAC ETL enhancements, productionizing AI/ML tools, and building monitoring metrics for AI/ML deployments at UCSF Health.

Required Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or related area and/or equivalent experience and training.
• 6 years of experience in roles with increasing responsibility designing, implementing, and maintaining complex AI/ML applications.
• Proficiency in MLOps, Python, SQL, and CI/CD.
• Experience using data analysis and machine learning tools such as Jupyter, Pandas, scikit-learn, NumPy/SciPy, and PyTorch.
• Demonstrated advanced knowledge of the full software development lifecycle.
• Advanced experience with Python, including writing clean, efficient, production-level code.
• Advanced experience with SQL, including SQLServer and PostgreSQL.
• Demonstrated experience deploying, monitoring, and maintaining AI/ML models and pipelines.
• Advanced experience with database systems, data warehousing solutions, and understanding of ETL pipelines.
• Advanced experience designing, building, or maintaining data infrastructure for efficient ML training and inference.
• Demonstrated experience working with MLOps, DevOps, and CI/CD toolsets.
• Experience developing complex, automated testing.
• Experience with cloud-based architecture on AWS, GCP, or Azure.
• Demonstrated effective communication and interpersonal skills, including the ability to communicate technical information to technical and non-technical personnel.
• Self-motivated with the ability to work independently and as part of a team, 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.

Technologies

• Python
• SQL
• CI/CD
• Jupyter
• Pandas
• scikit-learn
• NumPy
• SciPy
• PyTorch
• MLOps
• DevOps
• SQLServer
• PostgreSQL
• AWS
• GCP
• Azure

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.
• Familiarity with data visualization tools such as Tableau.
• Experience with Epic data structures.
• Epic Clarity Certification.
• Cloud Development certifications.

EPIC Data Models and Certification

• This role requires deep understanding of Epic data models including Clarity and Caboodle.
• Candidates must either have Epic Clinical/Clarity data model certification or be able to obtain certification shortly after onboarding.

Additional Job Information

• Grant funded, 18 month, Limited Appointment position.
• Certain terms and conditions of employment, including rate of pay and benefits, are subject to negotiation with the appropriate union.
• Position is flexible with 2 days on-site.
• Must be available for lab on-site meetings that may occur once per week or bi-weekly based on department needs.

Location, Salary, and Experience

• Location: San Francisco, CA (hybrid)
• Compensation: USD 101,000 - 216,000 per year
• Minimum experience: 6 years