AI Research Scientist

AI Research Scientist

The Office of Responsible AI (ORAI) at the University of Arizona is looking for an AI Research Scientist. This position will lead the development, oversight, and management of AI/ML and data science training initiatives across the University of Arizona. The incumbent will work onsite at the University of Arizona serving as a technical leader and consultant by developing predictive models, operationalizing generative AI frameworks, and applying advanced NLP and unstructured text analytics to extract strategic insights from complex datasets.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!

For more information about working at the University of Arizona and relocations services.

Location: Tucson Campus, Tucson, AZ USA

Contract type: Full Time

Number of Hours Worked per Week: 40

Job FTE: 1.0

Rate of Pay: $86,870 - $112,932

Compensation Type: salary at 1.0 full-time equivalency (FTE)

Grade: 11

Job Family: Research & Data Analysis

Job Function: Research

Career Stream and Level: PC4

Job Category: Research

Number of Vacancies: 1

Open Date: 7/22/2026

Open Until Filled: Yes

Contact Information for Candidates: Julie Emms | jemms

• Develop, validate, and deploy advanced statistical, machine learning, and deep learning predictive models to generate actionable insights for institutional and research stakeholders.
• Design and implement Natural Language Processing (NLP) pipelines, text vectorization methods, and unstructured data workflows to extract strategic value from large-scale textual datasets and institutional documents.
• Serve as an internal consultant for campus researchers and units, advising on model selection, feature engineering, fine-tuning LLMs with custom datasets, validation frameworks, and production deployment strategies.
• Systematically evaluate model performance utilizing advanced testing and verification frameworks to ensure accuracy, stability, and operational efficiency.

• Design, implement, and facilitate high-impact AI/ML, data science, and generative AI training programs, workshops, and self-paced learning modules tailored for various university audiences (faculty, staff, and students).
• Create rigorous educational materials focused on applied machine learning, prompt engineering frameworks, transformer dynamics, and responsible AI development.
• Establish institutional benchmarks and best practices for AI/ML education that seamlessly align with the Office of Responsible AI (ORAI) governance principles.
• Deploy robust formative and summative learning assessment tools to measure AI literacy gains, track training efficacy, and continuously refine programming to reflect evolving industry standards.

• Operationalize responsible AI practices across the institution, directly guiding stakeholders on algorithmic bias mitigation, model reproducibility, transparency, and data privacy.
• Partner with colleges, research units, and administrative divisions to identify emerging AI/ML needs, influence data governance policies, and develop collaborative, data-driven solutions.
• Translate highly complex, technical AI/ML and NLP concepts into accessible, strategic guidance and executive summaries for university leadership and non-technical audiences.
• Contribute actively to AI strategy alignment and knowledge exchange with external and internal academic, research, and industry partners.

• Draft and co-author high-quality, multidisciplinary grant proposals and technical funding applications to secure external resources for programmatic sustainability.
• Partner with cross-functional campus investigators to seamlessly integrate technical data specifications, AI/ML research objectives, budget justifications, and educational project milestones into compelling reviewer narratives.

• Comprehensive understanding of AI ethics, including bias mitigation, model reproducibility, transparency, data governance, and policy compliance.
• Skilled in drafting high-quality, multidisciplinary grant proposals.
• Skilled in utilizing real-world case studies, accessible analogies, and practical applications to help understand and ethically apply AI tools.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

• Bachelor's degree or equivalent advanced learning attained through…