Adjunct Instructor (Artificial Intelligence & Machine Learning)

• Improve the lives of students from across the nation through the power of education.
• Opportunity to give back through educating the next generation of tech experts.
• Experience the “light” turn on in your student’s eyes as you teach and they experience true understanding.
• Be a part of a computer science institution that focuses on creating software engineers that can DO, not just theorize.
• Develop your teaching/mentoring skills.

Faculty at Neumont University are responsible for educating students in accordance with the Neumont teaching methodology, which focuses on active learning and engaging students in the learning environment. Faculty members are also responsible for grading and providing valuable feedback to students in a timely manner, mentoring students in groups or individually, evaluating curriculum, adapting coursework and materials as necessary to meet student learning needs, and other activities related to effective instruction., * Implement best practices in teaching and project-based learning

• Submit all new teaching materials to Neumont vault upon completion of each course
• Work with supervisor to identify areas for personal development and course improvement
• Utilize feedback from mid-quarter and end-of-quarter evaluations to improve teaching
• Identify innovative teaching methods to solve curricular problems
• Teach material defined in the course description and syllabus
• Maintain and meet the listed student learning goals
• Utilize the Neumont LMS to keep an updated syllabus, course materials, and grades
• Provide a safe learning environment for students
• Answer and deal respectfully with student complaints and problems
• Use effective assessments that measure student learning
• Provide timely and accurate feedback to students’ assignments, exams, projects, etc.

• Ability to teach AI fundamentals to complete beginners in clear, accessible terms

• Familiarity with low-code AI tools, including Microsoft Azure ML Studio

• AI Data Modeling:

• Proficiency in SQL/SQLite and relational database design (entity-relationship modeling through normalization)
• Experience with dimensional modeling / data warehousing (star schemas, OLTP vs. OLAP)
• Understanding of how data modeling supports ML pipelines (feature stores, vector stores/embeddings, train/serve skew)
• Ability to teach query optimization, including indexes and reading query execution plans

• Strong working proficiency in Python, sufficient to review and debug student code live in class

• Machine Learning Foundations:

• Comfort teaching and evaluating algorithmic complexity (Big-O: time and space)
• Solid grounding in core ML concepts: supervised/unsupervised/reinforcement learning, overfitting, neural network fundamentals, * Solid theoretical grounding in reinforcement learning (MDPs, Bellman equations, dynamic programming)
• Hands-on experience with Monte Carlo methods, TD learning/SARSA, Q-learning, policy gradients, and DQNs
• Working knowledge of NumPy and PyTorch
• Ability to teach on-policy vs. off-policy tradeoffs and deep-RL stability concepts (replay buffers, target networks), * Bachelor’s or higher degree in computer science or a related field AND 4 years of CS related experience (or 8 years of CS related experience without a CS degree)
• Teaching experience preferred, but not required
• Ability to work within the U.S. without company sponsorship, We hire industry professionals and help them learn how to be good teachers. Our project-based curriculum means fewer lectures and more hands-on practice. Instructors must have at least 4 years of industry experience and a bachelor’s degree in a tech related field. An additional 4 years of outstanding experience and contributions to the field may be substituted for a formal degree.