University of Toronto
Faculty of Information
Sessional Lecturer
Winter Term 2027 ( January 2027 - April 2027 )
INF2205H - Designing Sustainable and Resilient Machine Learning Systems with MLOps
Course Description:
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 everchanging 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
Salary:
Sessional Lecturer I: $10,889
Sessional Lecturer I Long Term: $11,652
Sessional Lecturer II $11,652
Sessional Lecturer II Long Term: $11,924
Sessional Lecturer III: $11,924
Sessional Lecturer III Long Term: $12,202
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.
Application Deadline: June. 1, 2026
Application Process: Applicants must submit a CV and a completed CUPE 3902 Unit 3 application form in one pdf file to the attention of:
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.
