DeVry University strives to close our society’s opportunity gap and address emerging talent needs by preparing learners to thrive in careers shaped by continuous technological change. Through innovative programs, relevant partnerships, and exceptional care, we empower students to meaningfully improve their lives, communities, and workplaces.
Our colleague experience is an area of obsessive focus. At DeVry University, we care about you. Because, only through you can we deliver our unique Care Formula to our learners and partners.
Opportunity:
DeVry University focuses on developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm and a commitment to providing the finest practitioner-focused education. We are seeking primarily industry professionals to teach and share their knowledge and experience with undergraduate and graduate students in a variety of fields.
- Courses meet once or twice a week for eight weeks.
- Face-to-face interaction is blended with technology (such as online discussions and online assignments) for an enhanced learning environment.
- Faculty are responsible for facilitating student learning by teaching courses and programs in accordance with DeVry University requirements.
- Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives.
- All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction.
- DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion.
- As you explore this opportunity, we invite you to view this brief video highlighting how our faculty engage in meaningful student support.
Responsibilities:
- Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives.
- Organizes, prepares, and regularly revises and updates all course materials.
- Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students.
- Models effective oral and written communications that engage the students, provide clarity, and improve student learning.
- Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories.
- Ensures that the content and level of material included on exams correspond to the course terminal objectives.
- Demonstrates consistency and fairness in the preparation and grading of exams and provides timely feedback to students.
- Embraces and integrates the responsible use of AI technologies in the classroom to enhance teaching and learning outcomes.
- Demonstrates the ability to recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
- Completes other duties as assigned.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- 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.
- Applicants must upload unofficial graduate-level transcripts with their application.
- Degrees must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or by an international institution determined to hold equivalent accreditation.
- 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, combined with effective communication skills and the ability to explain complex technical topics to diverse learners.
- Knowledge of ethical, responsible, and secure AI practices, including awareness of data governance, bias mitigation, and responsible AI deployment.
- Faculty must have a commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
- Additional requirements driven by state licensing, institutional policy, or accreditation standards may apply.
Preferred Qualifications:
- Industry certifications in Python programming, artificial intelligence, machine learning, or data science (e.g., PCEP or equivalent).
- AI practitioner or engineer certifications (e.g., CAIP, Oracle GenAI, or comparable industry-recognized credentials).
- Experience with AI development frameworks and tools, such as machine learning libraries, model deployment platforms, or generative AI systems.
- Experience applying DevSecOps practices in AI or data-driven environments, including model lifecycle management and secure AI deployment.
- Experience with programmatic or regional accreditation processes, including outcomes assessment and curriculum alignment.
- Active membership or engagement in professional technology or AI-related organizations, contributing to ongoing industry awareness and innovation.
- Experience integrating AI-assisted learning tools, immersive technologies, or intelligent tutoring systems into post-secondary instruction.
- Two to five years of teaching experience at the post-secondary level, preferably in artificial intelligence, data science, programming, or emerging technology disciplines.
Pay:
Visiting Professor pay is based on level, credit hours taught per 8-week session, and location.
- Pay may vary in most states from $1500-$2700 per 8-week session.
- Pay in the states of AZ, CA, IN and PA is paid at an hourly rate of either $22.00/hour or $23.50/hour.
For Visiting Professor roles, we accept applications on an ongoing basis.
DeVry University offers benefit options for Visiting Professors, including:
- 401(k) and Roth Plan
- Paid Tuition Program
- Remote and Flex Work Options
- Paid Sick Time
- Technology Stipend
Benefits vary based on employment status. Part-time/Visiting Professors positions may not be eligible for all benefits.
We believe that a vibrant and collaborative workplace is essential to our educational mission and the success of our community.
We are committed to a workplace environment where all colleagues feel valued, respected, and supported.
Skills Required
- Doctorate in Artificial Intelligence, Computer Science, Data Science, Information Systems, or a closely related field
- At least 18 graduate credit hours in artificial intelligence, machine learning, data science, or a related computational discipline
- Unofficial graduate-level transcripts submitted with the application
- Degree from an appropriately accredited institution or internationally equivalent institution
- Three to five years of applied professional experience in artificial intelligence, machine learning, data science, intelligent systems, or related computational technologies
- Experience with AI-enabled software development, including machine learning pipelines, generative AI tools, data modeling, or full-stack applications integrating AI services
- Industry-recognized certifications or professional credentials relevant to artificial intelligence, machine learning, data science, or software development
- Strong AI subject matter expertise and ability to explain complex technical topics to diverse learners
- Knowledge of ethical, responsible, and secure AI practices, including data governance and bias mitigation
- Commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices
- Additional requirements related to state licensing, institutional policy, or accreditation standards
- Industry certifications in Python programming, artificial intelligence, machine learning, or data science
- AI practitioner or engineer certifications such as CAIP or Oracle GenAI
- Experience with AI development frameworks, machine learning libraries, model deployment platforms, or generative AI systems
- Experience applying DevSecOps practices in AI or data-driven environments
- Experience with accreditation processes, outcomes assessment, or curriculum alignment
- Active membership or engagement in professional technology or AI organizations
- Experience integrating AI-assisted learning tools, immersive technologies, or intelligent tutoring systems into post-secondary instruction
- Two to five years of post-secondary teaching experience
DeVry Bootcamp Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about DeVry Bootcamp and has not been reviewed or approved by DeVry Bootcamp.
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Leave & Time Off Breadth — Time off is described as generous, including good PTO, paid holidays, and volunteer days, and feedback suggests these benefits stand out among offerings.
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Wellbeing & Lifestyle Benefits — A broad set of lifestyle and ancillary benefits is listed, such as technology stipends, pet/legal insurance, and family-care services, indicating a wide-ranging perks ecosystem.
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Flexible Benefits — Remote/hybrid work options and various programmatic savings or payment flexibility are highlighted, suggesting adaptability to different employee and learner needs.
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