Machine Learning Engineer

UCSF Campus BU; San Francisco (CA); Hybrid; USD 101,000 - 216,000; Full time

Job summary

UCSF Campus BU is hiring a grant-funded Machine Learning Engineer for an 18-month Limited Appointment in San Francisco. The role focuses on building and maintaining data pipelines and infrastructure to deploy and monitor ML/AI tools, including HIPAC data and EHR productionization.

Responsibilities include leading data pipeline development, optimizing HIPAC, data integrations, ETL enhancements, and monitoring metrics across UCSF Health AI/ML deployments.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or related area, and/or equivalent experience or training.

Responsibilities

• Lead the development, implementation, and maintenance of data pipelines and infrastructure supporting deployment and monitoring of ML/AI tools.
• Manage and optimize HIPAC data and monitoring pipelines.
• Implement new data integrations and enhance HIPAC ETL functionalities.
• Productionize AI/ML tools created by UCSF data scientists and researchers.
• Design and implement metrics to monitor AI/ML tools deployed at UCSF Health.

Skills

MLOps

Python

SQL

CI/CD

Jupyter

Pandas

scikit-learn

NumPy/SciPy

PyTorch

DevOps

Cloud platforms

Education

Bachelor’s degree in CS/CE or related field

Master’s degree or PhD preferred

Tools

SQLServer

PostgreSQL

AWS

GCP

Azure

Tableau

Job description

UCSF Campus BU is hiring a grant-funded Machine Learning Engineer for an 18-month Limited Appointment to support the APeX Enabled Research (AER) team. This hybrid role in San Francisco focuses on building and maintaining data pipelines and infrastructure that enable the deployment and continuous monitoring of ML and generative AI tools, including work connected to HIPAC and productionization in the EHR environment.

Role Summary

This position will lead the development, implementation, and upkeep of data pipelines and supporting infrastructure for deploying and continuously monitoring Machine Learning (ML) and generative Artificial Intelligence (AI) tools within the UCSF APeX Enabled Research (AER) team. The role emphasizes managing and optimizing HIPAC data and monitoring pipelines, as well as productionizing AI/ML tools for use in UCSF Health’s EHR.

Key Responsibilities

• Lead the development, implementation, and maintenance of data pipelines and infrastructure supporting the deployment and continuous monitoring of ML and generative AI tools within the UCSF APeX Enabled Research (AER) team.
• Manage and optimize the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC).
• Implement new data integrations.
• Enhance HIPAC’s ETL functionalities.
• Productionize AI/ML tools created by UCSF data scientists and researchers.
• Design and implement metrics to continuously monitor AI/ML tools deployed at UCSF Health.
• Contribute across workstreams including data integrations, HIPAC ETL enhancements, AI/ML productionization, and monitoring metrics for AI/ML tools at UCSF Health.

Required Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or related area, and/or equivalent experience or 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 is required.
• Experience with data analysis and machine learning tools including Jupyter, Pandas, scikit-learn, NumPy/SciPy, and PyTorch.
• Demonstrated advanced knowledge of the full software development lifecycle.
• Advanced experience with Python, including clean, efficient, production-level 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 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 in AWS, GCP, or Azure.
• Demonstrated effective communication and interpersonal skills, including translating technical information for technical and non-technical audiences at multiple organizational levels.
• Self-motivated approach 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 or 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 (e.g., Tableau).
• Experience with Epic data structures.
• Epic Clarity Certification.
• Cloud Development certifications.

Epic Data Models and Certification

This role requires a deep understanding of Epic data models (Clarity and Caboodle). Successful candidates either have Epic Clinical/Clarity data model certification or are able to obtain the 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.
• Flexible schedule with 2 days on-site.
• Must be available for lab on-site meetings that may occur once per week or bi-weekly, based on departmental needs.

Location and Compensation

Location: San Francisco, CA (hybrid).
Salary: USD 101,000 - 216,000 per year.
Minimum Experience: 6 years.