AI Research Fellow​/Senior AI Policy Researcher

FT / PT Status – Full-Time Salary – $33.13 - $54.01 Hourly Wage Remote Work / In-Office – Hybrid Recruiter – Tehra Gorski | tgorski |  
Final date to receive applications – 6/24/2026

The Utah Department of Commerce, Office of Artificial Intelligence Policy, is seeking an AI Research Fellow to help drive technical, scientific, and policy research for Utah’s AI Learning Lab. This is an applied research and policy-translation role. The fellow’s work should directly inform regulatory decisions, legislative recommendations, regulatory mitigation agreements, and stakeholder strategy.

This role is technical and will rely heavily on statistical, machine learning, computer science, and empirical research skills. It will also require strong judgment, clear writing, and the ability to operate in a small multidisciplinary team alongside colleagues with policy, business, regulatory, and legal expertise. The right candidate will be comfortable taking ambiguous AI‑policy questions, structuring them, evaluating the evidence, talking to experts, and producing usable recommendations for decision‑makers.

The Office of Artificial Intelligence Policy was created in May 2024 as part of Utah’s effort to systematically develop sensible AI policy across major impact areas such as healthcare, education, finance, transportation, and consumer technology. Central to the Office is the AI Learning Lab, where industry experts, academics, regulators, and policymakers work toward appropriate regulatory responses to emerging AI applications. The Office also has authority to create regulatory mitigation agreements that allow responsible AI businesses to test products in Utah under structured conditions while the state gathers evidence and develops longer‑term policy solutions.

A hybrid telework schedule may be available, although regular in‑person work will be needed.

• Independently scope and execute research projects on emerging AI policy questions, including defining the question, identifying relevant technical and empirical evidence, interviewing experts, evaluating trade‑offs, and producing written recommendations for policymakers and regulators.
• Research technical aspects, capabilities, limitations, and societal impacts of AI technologies in support of the AI Learning Lab’s policy agenda.
• Evaluate evidence and forecasts concerning the impact of human‑AI interactions on health, economic activity, education, consumer welfare, and public institutions.
• Draft executive policy memos, legislative briefings, technical explainers, risk assessments, regulatory mitigation analyses, and recommendations for agency and legislative decision‑makers.
• Interface with business leaders, technologists, researchers, regulators, legislators, and lawyers to understand AI applications and help stakeholders develop well‑reasoned regulatory responses.
• Advise on the development of regulatory and legal standards as the Office’s recommendations move through agency, legislative, and stakeholder processes.
• Work with experts across disciplines to understand the benefits, risks, evidence gaps, and practical constraints associated with AI deployment in Utah.

• Deep technical knowledge of statistical methods, machine learning, and AI systems.
• Strong ability to translate technical, scientific, and empirical evidence into practical policy options for nontechnical decision‑makers.
• Familiarity with human‑subject research, qualitative and quantitative methods, medical or health sciences, social sciences, human‑computer interaction, or related empirical fields.
• Excellent problem‑solving ability, reliability, and independent judgment.
• Strong technical communication skills, including the ability to write clearly for policy, legal, regulatory, business, and technical audiences.
• Interest in AI policy, responsible innovation, regulatory design, and the business implications of AI deployment. Ability to work effectively in agile teams with diverse expertise and under conditions of uncertainty.

• Experience implementing, evaluating, or deploying AI systems, particularly in business, healthcare, government, or…