Description
UCLA HEALTH
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Description
This internship is embedded within UCLA Health Information Technology’s Office of Health Informatics and Analytics Teams, supporting analytics and AI/ML use cases across clinical, operations, finance, quality, and research domains. The Student Intern will gain hands on experience across the end to end data and AI lifecycle, including data engineering pipelines, feature platforms, MLOps practices, and high-performance computing (HPC) environments using cloud based technologies such as Azure, AWS and Databricks.
Qualifications
Required:
- Currently pursuing a undergraduate degree in Computer Science, Data Science, Engineering, or a related field
- Strong interest in data engineering, AI/ML, or compute infrastructure
- Comfortable working in collaborative, productionâoriented engineering teams
- Curious, detailâoriented, and motivated to learn enterpriseâscale systems in healthcare
Desired Technical Skills
- Programming Languages
- Python, SQL, and Java for data engineering and ML development
- Cloud & Data Platforms
- Experience or interest in Azure and Databricks for analytics and ML workloads
- Machine Learning & MLOps Concepts
- Feature engineering, feature stores, CI/CD, model deployment and monitoring
- Data Engineering Foundations
- Building pipelines, reusable workflows, APIs, and data quality mechanisms
- High Performance Computing & Infrastructure
- Exposure to HPC, AI/ML compute environments, and research infrastructure