Job Description
Onsite or Remote
Flexible Hybrid
Work Schedule
Monday-Friday 8am-5pm
Posted Date
04/13/2026
Salary Range : $17.9 - 47 Hourly
Employment Type
1 - Staff: Contract
Duration
10 weeks.
Job #
29673
Primary Duties and Responsibilities
SUMMARY STATEMENT :
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.
Internship Objectives
By the end of the program, interns will:
Contribute production‑ready code to data, ML, or infrastructure platforms
Understand how enterprise AI/ML systems are designed, deployed, and governed in healthcare
Collaborate with data engineers, ML engineers, architects, and researchers
Deliver tangible artifacts aligned with UCLA Health analytics initiatives
Key Focus Areas
Interns will work in one or more of the following areas, based on interest and team needs:
Data Analytics, Architecture & Engineering
Building Core data products and reusable data pipelines
Data orchestration workflows and APIs
Data quality and observability foundations
Feature engineering and feature store development
CI/CD for machine learning workflows
Monitoring, maintenance, and retraining of production ML models
Collaboration with data scientists to operationalize models
Compute & Research Infrastructure
Cloud platforms and HPC environments
AI/ML workloads for clinical and research analytics
Trusted research environments (e.g., ULEAD)
By the conclusion of the internship, each intern is expected to deliver:
A Production‑Grade Technical Artifact
Data pipeline, ML feature module, API, HPC configuration, or infrastructure component
Documentation & Knowledge Transfer
Technical documentation explaining design decisions, usage, and operational considerations
Quality & Reliability Contributions
Data quality checks, observability metrics, CI/CD integration, or validation scripts
Final Presentation or Demo
Walkthrough of project outcomes, lessons learned, and future improvement opportunities
Code Contribution to Team Repositories
Reviewed, tested, and version‑controlled code aligned with team standards
Job Qualifications
Required:
Currently pursuing a degree in Computer Science, Data Science, Engineering, or a related field
Comfortable working in collaborative, production‑oriented engineering teams
Curious, detail‑oriented, and motivated to learn enterprise‑scale systems in healthcare
Desired Technical Skills
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
As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer.
#J-18808-Ljbffr UCLA Health
Job Tags
Hourly pay, Contract work, Internship, Summer internship, Work at office, Remote work, Monday to Friday, Flexible hours