Machine Learning / Data Engineer

$125,500 - $188,300/Yr

Ucsf Medical Center - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

Hospitals

About the position

The Machine Learning / Data Engineer at UCSF Health will play a pivotal role in the development, implementation, and maintenance of data pipelines and infrastructure that support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools. This position is integral to the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure designed to facilitate the development and deployment of AI/ML tools, including large language models (LLMs) within the Electronic Health Record (EHR) system. The engineer will be responsible for managing and optimizing data and monitoring pipelines, implementing new data integrations, enhancing ETL functionalities, and productionizing AI/ML tools developed by UCSF data scientists and researchers. Additionally, the role involves designing and implementing metrics to continuously monitor the performance of AI/ML tools deployed at UCSF Health. Candidates for this position should have a strong background in software, machine learning, or data engineering, with at least two years of experience in implementing and maintaining AI/ML pipelines. Proficiency in MLOps, Python, SQL, and CI/CD is essential, along with a deep understanding of Epic data models (Clarity and Caboodle). Successful candidates will either possess or be able to obtain Epic Clinical/Clarity data model certification shortly after onboarding. The position offers a competitive salary range of $125,500 - $188,300, with placement dependent on experience and internal equity within the classification at UCSF. The Health AI team is part of the larger UCSF Health IT team, which focuses on improving patient care, clinician experience, and health system operations through advanced technology and analytics.

Responsibilities

• Lead the development, implementation, and maintenance of data pipelines and infrastructure for ML and AI tools.
• Manage and optimize data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC).
• Implement new data integrations and enhance HIPAC's ETL functionalities.
• Productionize AI/ML tools developed by UCSF data scientists and researchers.
• Design and implement metrics to continuously monitor AI/ML tools deployed at UCSF Health.

Requirements

• Bachelor's degree in a related area and/or equivalent experience/training.
• 2 years of experience designing, implementing, and maintaining complex AI/ML applications.
• Advanced experience with Python; ability to write clean, efficient, and production-level Python code.
• Advanced experience with SQL (e.g., SQLServer, PostgreSQL).
• Demonstrated experience working with MLOps, DevOps, and CI/CD pipeline toolsets.
• Experience with data analysis and machine learning tools such as Jupyter, Pandas, scikit-learn, Numpy/Scipy, PyTorch, etc.
• Experience in developing complex, automated testing.
• Experience with cloud-based architecture in platforms such as AWS, GCP, Azure.
• 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 advanced knowledge of full software development lifecycle.
• 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.

Nice-to-haves

• Master's degree or PhD in Computer Science, Computer Engineering, or related area and/or equivalent experience/training.
• Epic Clarity or Clinical Data Model certification.
• Experience with large language models and other generative AI technologies, especially in production environments.
• Familiarity with data visualization tools (e.g., Tableau).
• Experience with Epic data structures.

Benefits

• Comprehensive health insurance coverage.
• Retirement savings plan with 401k options.
• Paid time off and holidays.
• Tuition reimbursement for further education.
• Professional development opportunities.
• Flexible work arrangements including remote work options.