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

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

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)., 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., * 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, 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., + High School Diploma or Equivalent
• Associate Degree
• Bachelor’s Degree
• Master’s Degree
• Doctorate Degree 2. * How many years of related work experience do you have?
• Less than 6 years
• 6 years or more, but less than 9 years
• 9 years or more, but less than 12 years
• 12 years or more, but less than 15 years
• 15 years or more