Research AI Engineer

The Office of Responsible AI (ORAI) at the University of Arizona is accepting applications for a Research AI Engineer. The Research AI Engineer supports the research mission of the Arizona Institute for Artificial Intelligence and Society (AIS) and the Office of Responsible AI (ORAI) at the University of Arizona by maintaining and participating in the development of AI that advance research initiatives across the University of Arizona. This position supports integrating capabilities to deliver end-to-end AI prototypes from data preprocessing and model development to continuous improvement in production research environments. Guided by supervisors, the incumbent collaborates with researchers and research software engineers to support translating research questions into reproducible computational approaches. The position serves as a resource for campus AI adoption, supporting knowledge transfer, responsible AI practices, and the university's strategic AI initiatives.

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!

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• Assists with the development, testing, and maintenance of basic AI models and related research software to support faculty-led research initiatives.
• Supports data collection, cleaning, preprocessing, and organization activities using established procedures and guidance from senior team members.
• Implements experiment tracking, and automated retraining following established protocols.
• Assimilates routine AI models into research infrastructure using containerization (Docker/Kubernetes) and cloud platforms (AWS Bedrock, Azure ML, or equivalent) following established procedures.
• Works within appropriate AI frameworks, tools, and architectures based on research requirements.
• Assists in preparing technical documentation, reports, and research materials for project records, publications, and presentations.
• Supports routine research activities including data collection, preprocessing, evaluation, and analysis.
• Troubleshoots routine technical issues in research software and AI workflows and escalates more complex problems to senior staff as appropriate.
• Following established procedures maintains and optimizes research software applications, APIs, and tools aligned with research software engineering best practices.
• Applies established software development practices, including version control, testing, code review participation, and documentation standards to ensure reproducibility and sustainability of research code bases.
• Identifies of routine design or performance problems and implements recommended solutions.
• Supports integration of research software, datasets, and AI models within university research computing environments and infrastructure using established procedures.
• Troubleshoots routine technical issues in research software and AI workflows and escalates more complex problems to senior staff as appropriate.
• Follows established guidelines to assist with evaluating and testing new AI tools, software, and technologies under the direction of supervisors and senior technical staff.
• Contributes routine technical information and project updates for research proposals, reports, and other administrative documentation as assigned.
• Maintains awareness of emerging developments in AI and research software engineering and participates in relevant learning and training opportunities.

Knowledge, Skills, and Abilities:

• Knowledge of cloud-based AI/ML platforms (AWS Bedrock, Azure ML, Google Vertex AI) and containerization tools (Docker, Kubernetes).
• Knowledge of Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, or equivalent).
• Strong written and verbal communication skills.
• Ability to translate complex technical concepts for various research audiences.
• Ability to work independently with moderate guidance and manage multiple concurrent research projects.

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 in Computer Science, Data Science, Statistics, Engineering, or a related field; or equivalent advanced learning attained through professional-level experience.
• Minimum of 1 year of relevant work experience in AI/ML model development, data science, or research computing; or equivalent combination of education and work experience.

• Experience with large language models (LLMs), retrieval-augmented generation (RAG), or AI agent frameworks in research contexts.
• Experience with version control systems (Git/GitHub), collaborative development workflows, and reproducible research practices.
• Experience implementing MLOps practices including experiment tracking (MLflow, W&B), model registries, CI/CD pipelines, and model monitoring.