AI Intern, Summer 2026
About The Position
Internship candidates can expect a full-time onsite internship program, running from June 1, 2026 through August 7, 2026. This internship opportunity is offered in Milwaukee, WI. Carefully selected from universities, our interns bring distinctive ideas and perspectives to our organization. Our employees are passionate about building our emerging talent and future leaders. After application and initial screening conversation, interns are aligned interview and be hired to a specific team at NM based on their abilities and interests, providing exposure to real-world business perspectives through hands-on learning and significant work. In addition to their day-to-day tasks, interns participate in professional development workshops, senior leadership Q&A's, volunteer initiatives, networking/social events, and more! Overview We are building the next generation of employee enablement using AI — not as a concept, but as operational infrastructure. This role focuses on designing and implementing real AI-assisted workflows that improve how employees and leaders access information, complete tasks, and interact with HR systems. You will work directly on applied AI projects, building prototypes and internal tools that translate emerging capabilities into practical, usable systems. This is not a research internship. You will build and deploy working solutions used by internal teams. Applied AI Builder Intern (HR AI & Workflow Automation) Design and implement AI-assisted workflows that support HR and employee enablement use cases Build internal tools and agent prototypes Integrate AI capabilities with existing enterprise systems and knowledge sources Prototype solutions that automate repetitive workflows or improve access to information Document your designs and contribute reusable components and patterns for future development Collaborate with AI strategy, UX, and platform teams to translate real-world needs into technical implementations AI Systems & Knowledge Intern (AI Reliability, Evaluation & Knowledge Architecture) Help design and implement evaluation frameworks to assess AI output quality and reliability Analyze and improve how organizational knowledge is structured for AI retrieval and use Identify gaps, inconsistencies, or risks in AI-assisted workflows Help develop testing protocols, validation processes, and governance support tools Contribute to documentation and operational practices that support scalable AI adoption Collaborate with engineering, UX, and strategy teams to improve system reliability Bring Your Best! What this role needs.
Requirements
- Pursuing a degree in Computer Science, Data Science, Information Science, or related field
- Strong analytical thinking and attention to detail
- Strong programming skills (Python, TypeScript, or similar)
- Experience working with APIs and modern development tools
- Comfort working with structured data and systems
- Ability to work independently and translate ambiguity into structured approaches
Nice To Haves
- Familiarity with AI or LLM systems
- Experience working with data analysis, evaluation, or information architecture
- Interest in AI reliability, governance, system design, applied AI, or workflow automation
- Experience building automation tools, bots, or workflow systems
- Familiarity with cloud platforms or enterprise systems
- Ability to independently design and implement working technical solutions
- Strong problem-solving ability and attention to detail
Responsibilities
- Design and implement AI-assisted workflows that support HR and employee enablement use cases
- Build internal tools and agent prototypes
- Integrate AI capabilities with existing enterprise systems and knowledge sources
- Prototype solutions that automate repetitive workflows or improve access to information
- Document your designs and contribute reusable components and patterns for future development
- Collaborate with AI strategy, UX, and platform teams to translate real-world needs into technical implementations
- Help design and implement evaluation frameworks to assess AI output quality and reliability
- Analyze and improve how organizational knowledge is structured for AI retrieval and use
- Identify gaps, inconsistencies, or risks in AI-assisted workflows
- Help develop testing protocols, validation processes, and governance support tools
- Contribute to documentation and operational practices that support scalable AI adoption
- Collaborate with engineering, UX, and strategy teams to improve system reliability
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
