Visiting Professor for Artificial Intelligence Online
Remote · United States
Job Summary
Visiting Professor to teach AI-related courses for undergraduate and graduate students. Courses meet over an 8-week session with face-to-face learning blended with online discussions and assignments. Responsibilities include developing and updating syllabi and course materials, using appropriate online tools, modeling clear written and oral communication, publishing terminal objectives and assignment/exam schedules, ensuring alignment of exams with objectives, providing timely feedback on assessments, and integrating responsible AI practices into instruction. The role emphasizes teaching excellence, student support, and ongoing faculty development, with a focus on AI concepts, machine learning, data science, and related technologies. Pay is posted as hourly with variability by state, and remote/flex work options are available. A doctorate in AI/CS/DS/IS or related field is required, along with 3–5 years of applied AI experience, relevant certifications, and demonstrated instructional capability.
Required Qualifications
- A doctorate in Artificial Intelligence, Computer Science, Data Science, Information Systems, or a closely related field is required, with at least 18 graduate credit hours in artificial intelligence, machine learning, data science, or a related computational discipline.
- Three to five years of applied professional experience in artificial intelligence, machine learning, data science, intelligent systems, or related computational technologies.
- Demonstrated experience with AI-enabled software development, which may include machine learning pipelines, generative AI tools, data modeling, or full-stack application development integrating AI services.
- Industry-recognized certifications or professional credentials relevant to artificial intelligence, machine learning, data science, or software development.
- Strong subject matter expertise in AI concepts and technologies, with effective communication skills for diverse learners.
- Knowledge of ethical, responsible, and secure AI practices, data governance, bias mitigation, and responsible AI deployment.
- Commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
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