Assistant Teaching Professor and Associate Teaching Professor in the Paul G. Allen School of Compute

teaching faculty position at the rank of Assistant or Associate. This is a full-time position with a nine-month academic, 3-year appointment beginning September 16, 2027. We seek applicants who demonstrate commitment to excellence in teaching and service in a diverse and inclusive academic community. This position will split its time between (1) supporting the AI and Machine Learning Education graduate programs , based in the College of Engineering, with a range of teaching and curriculum-development opportunities; and (2) teaching a variety of undergraduate and graduate-level AI courses in the Allen School. The base salary range for this position will be $11,300 - $14,500 per month at the Assistant Teaching Professor level or $12,300 - $17,500 per month at the Associate Teaching Professor level, commensurate with experience and qualifications, or as mandated by a U.S. Department of Labor prevailing wage determination. Other compensation associated with this position may include a one-time relocation incentive. The successful candidate will be expected to contribute to the development of internationally recognized programs and provide innovative, high-quality teaching at the graduate and undergraduate levels, including incorporating diverse perspectives into their teaching and service endeavors and using evidence-based practices to support learning outcomes of students from a wide variety of backgrounds. The candidate would also be expected to collaborate with members of the Allen School, College of Engineering, and other faculty and staff within the University, participate in the administration of graduate programs, and participate in the teaching, mentoring, and training of graduate and undergraduate students. Positive factors for consideration include, but are not limited to, a PhD in a relevant area, previous experience training professional engineers, interfacing with industry partners, developing new programs, and developing pedagogical or evaluative tools. Responsibilities In the College of Engineering, teach courses in the AI, machine learning, and computing curriculum (e.g., Foundations of AI/ML for Engineering, Physics-Informed Machine Learning, Applied Optimization, AI & ML Capstone) with an emphasis on students’ success and mentoring teaching assistants. In the Allen School, teach undergraduate and graduate courses in AI as appropriate based on the candidate’s expertise and interest (e.g., machine learning and other sub-fields of AI such as computer vision, natural language processing). Teaching Allen School courses beyond AI may also be a possibility. Contribute to the Allen School, College of Engineering, and University through leadership and service roles. Contribute to educational scholarship through course development, engagement with educational communities, and possibly research. Promote an inclusive community through teaching, service, and possibly scholarship. Qualifications Applicants for this teaching faculty position must meet the following minimum qualifications: Master’s degree or foreign equivalent in computer science, engineering, or a related discipline. Demonstrated record of excellence in teaching as an instructor or teaching assistant. Technical expertise in artificial intelligence and/or machine learning as applied to engineering, such as design, optimization, control, and/or modeling of engineering systems To ensure full consideration of your application, please submit all materials no later than November 15, 2026. Applications will only be accepted via Interfolio: Link. The position will remain open until filled. Applications should include the following materials: A cover letter of no more than 2 pages detailing your interest in the position, relevant qualifications, and experiences. A curriculum vitae. A statement of teaching philosophy and evidence of teaching effectiveness. Applications for Associate Teaching Professors should address course and curriculum design. 3 letters of recommendation to be submitted at the time of application. Applicants should articulate how their past experiences and/or future plans in research, teaching, mentoring, and/or service promote a sense of belonging and foster a welcoming and inclusive environment. Rubric Our evaluation rubric is publicly available so that candidates and their letter writers have a better sense of what they can include and highlight in their application materials.We welcome applicants from all backgrounds and with a variety of experiences and perspectives. Positive factors for consideration include, but are not limited to, candidates who meet the threshold for a Good rating in at least two rubric items. Rubric Link (https://docs.google.com/spreadsheets/d/1PdwM2f3yeZmQpf5McaWIlCcVPhVHxAxKtiJCoyLskZ0/edit?gid=0#gid=0) Equal Employment Opportunity Statement Equal Opportunity The University of Washington is committed to fostering an inclusive, respectful and welcoming community for all. As an equal opportunity employer, the University considers applicants for employment without regard to race, color, creed, religion, national origin, citizenship, sex, pregnancy, age, marital status, sexual orientation, gender identity or expression, genetic information, disability, or veteran status consistent with UW Executive Order No. 81 . Benefits Information The University is committed to providing excellent benefits to our faculty. For a summary of available benefits, please see UWHR benefits information . Privacy Notice Your application materials may be used for employment consideration and shared in accordance with UW’s Privacy Policy. Disability Services The University of Washington is committed to providing access and reasonable accommodation in its services, programs, activities, education, and employment for individuals with disabilities. To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or dso@uw.edu.