Job Description

Details

Open Date 09/18/2026 Requisition Number PRN46243B Job Title Artificial Intelligence (AI) / Machine Learning (ML) Engineers Working Title Speculative Design Researcher, Brain-Computer Interfaces Career Progression Track P00 Track Level P4 - Advanced, P3 - Career, P2 - Developing FLSA Code Computer Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary VP Area Academic Affairs Department 00065 - Elect & Computer Engineering Location Campus City Salt Lake City, UT Type of Recruitment External Posting Pay Rate Range 80,000 to 200,000 Close Date 12/31/2026 Priority Review Date (Note - Posting may close at any time) 10/02/2026 Job Summary

About the role

This is a research-driven design role focused on the next generation of human interaction with brain-computer interfaces. The person in this role will imagine how people will interact with technology as BCIs move toward becoming as common as the smartphone, and, just as importantly, prove that vision through hands-on prototyping. This is speculative design, but not vision for its own sake. The work is to picture a next-generation system, backtrack to what we can build now to move toward it, and think through what that future would mean for society if it arrives.

The role sits at the intersection of speculative vision and hands-on execution. It requires a designer who can define a new interaction paradigm and then build the working prototypes that bring it to life and test whether it holds up. The emphasis is on making, not only thinking: concepts become prototypes, and prototypes become the evidence for the vision.

Because the systems imagined in this role are intelligent, personal, and context-aware, the work spans interaction design, information architecture, and the design of how people communicate with an intelligent agent. The ideal candidate is as comfortable organizing complex information and memory into a coherent system as they are crafting the moment-to-moment experience of using it, and can weigh the broader implications of these technologies for people and society.

Artificial Intelligence (AI) / Machine Learning (ML) Engineers

Research, design, develop, test, and support artificial intelligence (AI) and machine learning (ML) frameworks and models. Leverage AI/ML techniques to answer business questions, support business strategies, and deliver valuable quantitative insights to improve products. Develop sophisticated algorithms to automate processes and tasks. Collaborate with internal stakeholders to understand business and technical needs. Code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR). Remain up to speed on cutting edge research for AI technology and concepts.

Learn more about the great benefits of working for University of Utah: benefits.utah.edu

Responsibilities

Responsibilities

• Envision next-generation interaction paradigms for a future in which brain-computer interfaces are mainstream, and backtrack to what can be built today to move toward it.
• Build working software prototypes that make these concepts tangible, testable, and convincing.
• Design how people communicate intent to an intelligent, context-aware system, and how that system understands, organizes, and acts on it.
• Design the information architecture behind such a system: how information is captured, connected, retrieved, and, when appropriate, allowed to fade.
• Explore and demonstrate capabilities that only a BCI makes possible, beyond what current devices can do.
• Design for the realities of neural input, including uncertainty, limited speed, and feedback that does not depend on a screen.
• Conduct design research to understand how people think, remember, and want to interact with technology.
• Consider the societal implications of these emerging technologies and factor them into design decisions.
• Produce concepts, design fiction, prototypes, and narratives that communicate the vision clearly.
• Develop a roadmap that connects the long-term vision to near-term, buildable steps

Minimum Qualifications

EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor’s degree = 4 years of directly related work experience).

Department may hire employee at one of the following job levels:

Artificial Intelligence (AI) / Machine Learning (ML) Engineer, III: Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience.

Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IV: Requires a bachelor’s (or equivalency) + 8 years or a master’s (or equivalency) + 6 years of directly related work experience.

Artificial Intelligence (AI) / Machine Learning (ML) Engineer, V: Requires a bachelor’s (or equivalency) + 10 years or a master’s (or equivalency) + 8 years of directly related work experience.

Preferences

Preferred qualifications

• Experience designing interactions with AI agents or other intelligent, context-aware systems
• Experience with information architecture, knowledge organization, or systems for memory and retrieval
• Experience designing voice, audio, or screenless interfaces, and predictive or context-aware interaction
• Experience designing for assistive technology, or for people with paralysis or speech loss
• Strong skills in storytelling and turning complex systems into clear narratives and visualizations
• Ability to think critically about the societal implications of emerging technologies
• A demonstrated bias toward initiative, experimentation, and exploring unconventional ideas

Type Benefited Staff Special Instructions Summary Additional Information

The University is a participating employer with Utah Retirement Systems (“URS”). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS’ post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.

This position may require the successful completion of a criminal background check and/or drug screen.

The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.

Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.

Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran’s status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.

To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX (OEO). More information, including the Director/Title IX Coordinator’s office address, electronic mail address, and telephone number can be located at the: University of Utah Non‑Discrimination page.

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As per University of Utah policy 5-108: Transfer of Benefits Eligible Staff Members, a new hire to the University of Utah who is still serving a 12 month probationary period will not be hired into another University of Utah job (a transfer) until the successful completion of the probationary period.