UCSF is looking to solve the problem of developing, implementing, and maintaining data pipelines and infrastructure to support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools within the APeX Enabled Research (AER) team.
Requirements
- Proficiency in MLOps, Python, SQL, and CI/CD.
- Deep understanding of Epic data models (Clarity and Caboodle).
- Advanced experience with Python; ability to write clean, efficient, and production-level Python code.
- Advanced experience with SQL (e.g., SQLServer, PostgreSQL).
- 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.
- Experience with cloud-based architecture in platforms such as AWS, GCP, Azure.
Responsibilities
- 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.
- 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.
- Managing and optimizing the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC).
- Deploying, monitoring, and maintaining AI/ML models and pipelines.
Other
- Bachelor's degree in Computer Science, Computer Engineering, or related area and/or equivalent experience/training.
- 5+ years of experience in positions of increasing responsibility designing, implementing, and maintaining complex AI/ML applications.
- 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.
