Sessional Lecturer, INF2205H - Designing Sustainable and Resilient Machine Learning Systems

Sessional Lecturer, INF2205H - Designing Sustainable and Resilient Machine Learning Systems University of Toronto Faculty of Information

Sessional Lecturer

Winter Term 2027 ( January 2027 - April 2027 )

Decision-makers in modern organizations rely on machine learning systems to infer insights from information by analyzing meaningful patterns in the connections and associations within data. Leaders in many sectors of our economy and society utilize these systems to support evidence-informed decision-making using techniques such as regression, classification, clustering, and collaborative filtering. This course, INF2205H, examines state of the art techniques and technologies related to MLOps (Machine Learning Operations). MLOps refers to the application of continuous delivery and continuous integration (CI/CD) principles and practices for designing sustainable and resilient machine learning systems. MLOps helps designers of machine learning systems to address the challenge associated with the ever-changing nature of data that is conveyed by the adage “model drifts as data shifts”. Students will use frameworks and techniques for architectural modeling, analysis, and design to understand and apply theoretical and practical aspects of MLOps.

Estimate of the course enrolment:

50

Estimate of TA Support:

Estimate of 75 hours with enrollment of 36 or greater. Allocation of TA hours, if any, will be based on enrolment numbers.

Class Schedule:

TBD. You are required to be located in geographical proximity to the applicable University premises in order to attend and perform your duties on University premises as of the Starting Date.

Sessional dates of appointment:

January 1, 2027 - April 30, 2027

Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Qualifications:

Preferably candidates will have a completed, or nearly completed, PhD degree in an area related to the course or a Master’s degree plus extensive professional experience in an area related to the course. Teaching experience is preferred.

Brief description of duties:

Preparing course materials; delivering course content (e.g., seminars, lectures, and labs); developing and administering course assignments, tests & exams; grading; holding regular office hours.

Nafiseh Yazdian, Administrative Coordinator Faculty of Information, 140 St. George Street University of Toronto sessional.ischool@utoronto.ca

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.

Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP .

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca .

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