Intern

Job Summary

The Center for High Performance Computing (CHPC) is seeking students to fill part-time positions that support CHPC's mission to enable research and innovation through advanced computing infrastructure, technical services, and user support at the University of Utah. Program participants—including undergraduate students, graduate students - receive hands-on experience in a professional technical environment. Positions are structured to provide meaningful project work, defined learning or professional-development objectives, and supervised access to CHPC systems appropriate to the role.

This position will work with the User Services team, which consists of 7 MSc and PhD level scientific consultants, to assist with research, development and deployment of AI tools for CHPC users and researchers. This includes research on and evaluation of the latest open source large language models (LLMs), setting them up in research and production environment at the CHPC, interfacing them with tools like code development UIs, chatbots and agents, and fine-tuning them with CHPC related information such as documentation, recorded user interactions, job logs, etc. Along with using and developing AI tools, the position will allow to learn about and use a high performance computing (HPC) environment and the services that are associated with it.

Responsibilities

• Researching latest developments in generative AI, including LLMs and tools that use them
• Deploying open source genAI models and tools locally
• Continue development and fine-tuning of locally run chatbots and agents
• Participating in onboarding, training, mentoring, and regular check-ins with a supervisor
• All duties are assigned in accordance with CHPC role-based access controls, data security requirements, and the participant's experience level and program track.

Minimum Qualifications

Strong communication and organizational skills. Ability to follow documented procedures and work independently with supervision. Reliability, professionalism, and attention to detail. Willingness to learn new technical or operational skills.

Preferences

Basic understanding of AI technologies. Technical experience with LLMs. Programming skills in Python and/or other languages that LLM interfaces use.