AI Application Development Intern

NorthStar Medical Radioisotopes•Beloit, WI

1d•Onsite

About The Position

The AI Application Development Intern is responsible for designing, developing, testing, and deploying internal software tools and applications leveraging artificial intelligence and automation technologies. This role focuses on translating defined business requirements into functional applications that improve operational efficiency, enable data-driven decision making, and support scalable digital solutions across the organization. Working in close collaboration with Process Excellence teams, the intern will rapidly build practical, production-ready tools, validate performance against defined use cases, and support deployment into real-world environments. The role requires a hands-on, solutions-oriented mindset in a fast-paced and evolving technical landscape.

Requirements

Pursuing a Bachelor’s or Master’s in Computer Science, Data Science, or a related field (Junior+ strongly preferred)
Basic programming skills (Python or similar) and familiarity with core development fundamentals (coding, Git, testing basics)
Applied experience using AI/ML tools, APIs, or automation in a project setting
Completion of at least one hands-on project involving AI, automation, or data processing (coursework projects acceptable)
Ability to solve problems, debug issues, and work from defined requirements
Strong communication skills and ability to work in a team environment

Nice To Haves

Experience developing and deploying AI-enabled applications (not just models)
Familiarity with large language models (LLMs), prompt engineering, or AI orchestration tools
Experience with Microsoft Power Platform, Azure, or similar technologies
Exposure to regulated or quality-controlled environments
Demonstrated interest in process improvement and operational efficiency

Responsibilities

Design, develop, and implement AI-enabled applications and tools based on defined requirements.
Collaborate with cross-functional teams to refine and iterate solutions, resolving bugs, issues, and improving features.
Evaluate and deploy new and improved AI development tools and workflows.
Deploy applications and support adoption across teams.
Test, debug, and validate applications for reliability and performance. Coordinate with validation teams and support software validation practices as required.