AI Research Scientist

Advanced AI/ML Development & Technical Consulting

• 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.

Educational Programming, Curriculum Design & Assessment

• 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.

Responsible AI, Governance & Strategic Alignment

• 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.

Grant Writing & Program Sustainability

• 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.

Knowledge, Skills, and Abilities:

• 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.