Artificial Intelligence (AI) Research Scientist (25 Hours/12 Months)

Dr. Robert K. Jabs School of Business; Riverside (CA); On-site; USD 42,000 - 76,000; Part time

Job summary

The AI Research Scientist role at the University is a grant-funded, part-time position within the College of Engineering. You will research, design, develop, and deploy advanced AI solutions, collaborating with faculty, students, and external partners to advance sponsored research and real-world applications.

You will contribute to technical research, software development, publications, and demonstrations while mentoring student researchers and supporting experiential learning.

Qualifications

• PhD required in AI/ML/CS or related field.
• Experience in research and translational AI projects.
• Strong publication record desirable.

Responsibilities

• Research, develop, validate, and deploy AI models and data pipelines.
• Design scalable AI solutions across cloud and hybrid environments.
• Develop RAG frameworks for enhanced information retrieval and reasoning.
• Lead LLM evaluation, benchmarking, and deployment.
• Mentor student researchers and collaborate with partners.

Skills

Python

PyTorch

NLP

RAG

Knowledge graphs

LLMs

Speech tech

Cloud deployment

MLOps

Education

PhD in AI/ML/CS

Tools

Neo4j

LangChain

DSPy

TensorFlow

Job description

Summary

The AI Research Scientist role is a grant-funded, part-time position within the College of Engineering that supports the research, design, development, and deployment of advanced artificial intelligence solutions in support of the Defense Innovation Network Assistant (DINA) initiative. The position conducts applied and translational research in machine learning, natural language processing (NLP), retrieval-augmented generation (RAG), intelligent agents, knowledge graphs, speech technologies, and AI-enabled decision support systems. Working collaboratively with faculty researchers, engineers, students, and external partners, the AI Research Scientist develops innovative AI technologies that advance sponsored research objectives and support real-world applications. The position contributes to technical research, software development, grant initiatives, publications, technology demonstrations, and deployment of scalable AI solutions while mentoring student researchers and fostering hands‑on experiential learning opportunities.

Grant‑Funded Position Definition

This position is funded, in whole or in part, through external grant funding. Continued employment is contingent upon the availability of grant funds and the ongoing operational needs of the University. Should grant funding be reduced, exhausted, discontinued, or otherwise become unavailable, the University reserves the right to modify, reduce, or eliminate the position, including changes to duties, work hours, or employment status, in accordance with applicable policies and business needs. While the University may evaluate opportunities to continue the position through alternative funding sources, no guarantee of continued employment exists beyond the availability of designated grant funding. Decisions regarding the continuation, modification, or conclusion of the position remain within the sole discretion of the University.

Essential Duties And Responsibilities

include the following. Other duties may be assigned.

• Research, develop, validate, and deploy AI models, algorithms, and data pipelines for processing large-scale structured and unstructured datasets using machine learning, natural language processing, semantic search, and knowledge graph technologies.
• Design, implement, optimize, and maintain secure, scalable, and high-performance AI solutions across cloud and hybrid computing environments, including Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP).
• Develop, enhance, and maintain retrieval-augmented generation (RAG) frameworks to improve information retrieval, contextual reasoning, and intelligent recommendations.
• Design and implement solutions utilizing knowledge graphs, vector databases, vector search technologies, and related architectures to support advanced decision support systems and intelligent applications.
• Lead the development, fine‑tuning, evaluation, benchmarking, and optimization of large language models (LLMs) and other AI technologies to support research and operational objectives.
• Design, build, and deploy AI-powered agents capable of executing workflows, automating complex tasks, and delivering context‑aware insights and recommendations.
• Develop, integrate, and maintain Speech‑to‑Text (STT), Text‑to‑Speech (TTS), and related conversational AI technologies and APIs.
• Implement secure AI development practices, data governance controls, privacy safeguards, and cybersecurity measures supporting sensitive and enterprise‑level environments.
• Collaborate with faculty, software engineers, data scientists, students, and external stakeholders to advance sponsored research initiatives and develop innovative AI‑enabled solutions.
• Conduct applied research, evaluate emerging AI technologies, and identify opportunities for innovation, process improvement, and technology advancement.
• Prepare technical reports, research summaries, presentations, publications, and other project deliverables required by funding agencies, sponsors, University leadership, and project stakeholders.
• Maintain compliance with grant requirements, University policies, research protocols, data security standards, and applicable regulatory requirements governing sponsored research activities.
• Assist with proposal development, grant support activities, and sponsored research initiatives as assigned.
• Mentor student researchers, graduate assistants, and project team members by providing technical guidance, research mentoring, and professional development support.
• Contribute to scholarly dissemination activities, including publications, presentations, conferences, technical demonstrations, and other research communication efforts, as appropriate.
• Perform other duties and special projects as assigned in support of departmental, grant, and University objectives.

Supervisory Responsibilities

This position does not have direct supervisory responsibilities. However, the incumbent may provide project leadership, technical direction, mentorship, and research guidance to student researchers, graduate assistants, and project team members.

Other Knowledge Skills And Abilities

To perform this position successfully, an individual must be able to effectively carry out all essential duties. The following requirements outline the knowledge, skills, and abilities needed for the role:

• Demonstrated commitment to living out and upholding the University’s Christ‑centered mission and values.
• Advanced knowledge of artificial intelligence, machine learning, deep learning, and modern AI architectures.
• Expertise in natural language processing (NLP), retrieval‑augmented generation (RAG), semantic search, knowledge graphs, and graph‑based reasoning systems.
• Experience designing, developing, and deploying enterprise‑scale AI applications and intelligent decision support systems.
• Advanced proficiency in Python and modern AI development frameworks, such as PyTorch, TensorFlow, LangChain, DSPy, or comparable technologies.
• Experience with Neo4j, vector databases, vector search technologies, and knowledge management architectures.
• Experience with large language models (LLMs), foundation models, agentic AI systems, and AI workflow orchestration.
• Knowledge of Speech‑to‑Text (STT), Text‑to‑Speech (TTS), and conversational AI technologies.
• Experience with Microsoft Azure, AWS, GCP, and cloud‑native AI solution development.
• Understanding of MLOps, model deployment, monitoring, evaluation, explainability, and responsible AI practices.
• Knowledge of cybersecurity principles, data governance, privacy regulations, and secure AI development methodologies.
• Strong analytical, problem‑solving, communication, and project management skills.
• Demonstrated ability to work effectively within interdisciplinary teams and collaborative research environments.
• Ability to mentor students and communicate complex technical concepts to diverse audiences.
• Ability to manage multiple priorities, deadlines, and project deliverables in a dynamic research environment.

Physical Demands

The physical demands described herein are representative of those required to successfully perform the essential functions of this position. While performing the duties of this job, the employee is regularly required to sit, stand, walk, speak, hear, and use hands and fingers to operate a computer, keyboard, and other standard office equipment. The employee must possess sufficient visual acuity to read printed materials, analyze electronic data, and perform computer‑based work. Effective communication in person, virtually, and by telephone is required. Occasional lifting, carrying, or moving of materials weighing up to 15 pounds may be required. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of the position.

Work Environment

The work environment characteristics described herein are representative of those encountered while performing the essential functions of this position. Work is primarily performed in a professional office, laboratory, or research environment utilizing computer and information technology systems. Noise levels are generally moderate and consistent with a professional office setting. The position may require participation in virtual meetings, collaborative research activities, conferences, training sessions, and occasional on‑campus events. Minimal exposure to adverse environmental conditions or health and safety hazards is expected.

Education and/or Experience

A Ph.D. from an accredited institution in Artificial Intelligence, Machine Learning, Computer Science, Computer Engineering, Data Science, Electrical Engineering, Natural Language Processing, or a closely related field is required.

One (1) to five (5) years of post‑doctoral, industry, academic, or applied research experience in artificial intelligence, machine learning, or related technologies is preferred. Equivalent combinations of education, research, and professional experience that demonstrate the knowledge, skills, and abilities necessary to perform the essential functions of the position may be considered.

Experience participating in interdisciplinary research and development initiatives involving advanced AI technologies is highly desirable.

Preferred Qualifications

• Experience developing and deploying enterprise‑scale AI applications and decision support systems.
• Record of scholarly achievement through publications, presentations, patents, or other recognized research contributions.
• Experience with transformer‑based architectures and foundation models, including GPT, Claude, Gemini, Llama, Mistral, BERT, DSPy, STORM, or comparable technologies.
• Experience in retrieval‑augmented generation (RAG), agentic AI systems, vector databases, LLM fine‑tuning, and production AI deployments.
• Experience with MLOps practices, model governance, and monitoring frameworks.
• Experience supporting sponsored research, grant‑funded initiatives, proposal development, or externally funded projects.
• Experience collaborating with government, defense, industry, or academic research partners.