Full Time Adjunct Faculty, MS Applied Artificial Intelligence

About the role

The Shiley-Marcos School of Engineering at the University of San Diego (USD) invites applications for a full-time adjunct faculty in the Master of Science in Applied Artificial Intelligence (MS-AAI) program, with an appointment beginning in the Spring 2027 semester, which begins on January 2, 2027. This is an on-campus position requiring the selected candidate to reside in or relocate to the San Diego area.

Duties And Responsibilities

• Demonstrate a strong commitment to teaching excellence in an applied graduate program.
• Deliver engaging instruction in 7-week, in-person course formats.
• Provide timely, constructive feedback and meaningful engagement with graduate students.
• Integrate industry experience, real-world case studies, and emerging AI practices into the teaching curriculum.
• Mentor and advise graduate students on academic progress, career planning, and capstone project development.
• Uphold USD’s Vision, Mission, and Core Values, including academic excellence, community, ethical conduct, and compassionate service.
• Maintain high standards of academic integrity and student performance.
• Collaborate with the Academic Program Director and Program Coordinator on course development and continuous improvement.
• Participate in departmental and university service and marketing activities as appropriate.

Special Conditions Of Employment

• Candidates must be authorized to work in the United States.

Job Requirements

• Minimum Qualifications: Master’s degree or higher in Artificial Intelligence, Computer Science, Data Science, Statistics, Electrical and Computer Engineering, or a closely related quantitative field.
• Demonstrated industry experience related to AI or applied research experience in artificial intelligence or machine learning.
• Strong foundations in machine learning principles, probability, statistics, and linear algebra relevant to deep learning and large language models.
• Strong interpersonal, collaborative, and professional communication skills.
• Commitment to equity, inclusion, student engagement, and inclusive teaching practices.

Preferred Qualifications

• Prior university-level teaching experience, ideally in in-person, project-based, or experiential learning environments.
• Industrial experience in AI engineering, ML engineering, deep learning, generative AI, LLM development, computer vision, or MLOps/model deployment.
• Proficiency in developing and deploying modern AI/ML systems, including expertise in core languages (e.g., Python) and frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, AWS SageMaker, and vector databases.
• Experience integrating ethical frameworks, responsible AI principles, and real-world case studies into teaching.
• Experience mentoring graduate students or supervising capstone projects.