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

University of Toronto•Saint George, UT

1h•Onsite

About The Position

The University of Toronto Faculty of Information is seeking a Sessional Lecturer for the Winter Term 2027 (January 2027 - April 2027) to teach INF2205H - Designing Sustainable and Resilient Machine Learning Systems with MLOps. This course examines state-of-the-art techniques and technologies related to MLOps (Machine Learning Operations), which applies continuous delivery and continuous integration (CI/CD) principles to design sustainable and resilient machine learning systems. The course will help students address the challenge of 'model drifts as data shifts' by using frameworks and techniques for architectural modeling, analysis, and design to understand and apply theoretical and practical aspects of MLOps. The estimated course enrollment is 50 students, with an estimated 75 hours of TA support if enrollment is 36 or greater. The class schedule is to be determined. The lecturer must be located in geographical proximity to the University premises to perform duties on-site.

Requirements

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
Must be located in geographical proximity to the applicable University premises in order to attend and perform duties on University premises as of the Starting Date.