Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps

University of Toronto Job Offer

Faculty of Information

Position: Sessional Lecturer

Winter Term 2025 (January - April)

Course: 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 by analyzing meaningful patterns in data. Leaders in various sectors utilize these systems for evidence-informed decision-making using techniques such as regression, classification, clustering, and collaborative filtering. This course explores cutting-edge MLOps (Machine Learning Operations) techniques and technologies. MLOps includes the application of continuous delivery and continuous integration (CI/CD) principles, essential for designing sustainable and resilient machine learning systems. It addresses challenges like "model drifts as data shifts." Students will learn frameworks and techniques for architectural modeling, analysis, and design to grasp theoretical and practical aspects of MLOps.

Estimate of Course Enrolment: 35

Estimate of TA Support: None anticipated. Estimate of 75 hours if enrollment reaches 36 or more. TA hours allocation will be based on enrolment numbers.

Class Schedule: TBD. You must be located near the University premises to attend and perform your duties on-site from the starting date.

Sessional Dates of Appointment: January 1, 2025 - April 30, 2025

Salary:

• Sessional Lecturer I: $10,300
• Sessional Lecturer I Long Term: $10,764
• Sessional Lecturer II: $11,021
• Sessional Lecturer II Long Term: $11,227
• Sessional Lecturer III: $11,279
• Sessional Lecturer III Long Term: $11,485

Please note that in case of any variance in rates as per the collective agreement, the rates mentioned in the agreement will prevail.

Qualifications:

Preferred candidates will have a PhD degree (completed or near completion) related to the course or a Master’s degree with extensive professional experience in the relevant area. Teaching experience is preferred.

Description of Duties:

Responsibilities include preparing course materials, delivering course content (seminars, lectures, and labs), developing and administering course assignments, tests, exams, grading, and holding regular office hours.

Application Deadline: June 27, 2024

Application Process:

Interested applicants must submit a CV and a completed CUPE 3902 Unit 3 application form in one PDF file to:

Melissa Szopa, Administrative Coordinator, Academic

Faculty of Information, 140 St. George Street, University of Toronto

Email: [email protected]

This job posting complies with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to candidates advanced to the rank of Sessional Lecturer II and Sessional Lecturer III as per Article 14:12.

Company Name: University of Toronto

Job Title: Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps