TA (CUPE) - MIA5150 D - Winter 2027

University of Ottawa; Ottawa; On-site; CAD 47,000 - 73,000; Part time

Job summary

University of Ottawa seeks a Teaching Assistant/Demonstrator/Lab Monitor for the course Topics in Interdisciplinary Artificial Intelligence (MIA5150). The role runs Jan 4, 2027 to Apr 30, 2027 at Main Campus, 130 total hours, with hourly rates for Undergraduate and Graduate students.

The TA will assist with tutorials, labs, and office hours, grade assignments, proctor exams, and support students in Generative AI concepts and related tools. Strong Python and AI framework experience is expected.

Qualifications

• Completed an equivalent graduate-level course in Generative AI and LLMs with grade A or higher.
• Strong understanding of Generative AI and LLM concepts including Transformers, prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and multimodal AI.
• Proficiency in Python and experience with modern AI/ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, and vector databases).
• Familiarity with LLM APIs and deployment frameworks.
• Excellent communication with the ability to effectively support students during tutorials, labs, and office hours.
• Previous teaching assistant experience.
• Familiarity with agentic AI concepts and multi-agent frameworks.
• Relevant industry experience developing or applying Generative AI or LLM-based applications.

Responsibilities

• Support students during tutorials, labs, and office hours.
• Assist with grading and notation tasks for course assessments.
• Provide proctoring and supervision during labs and exams.
• Contribute to preparation and research discussions as needed.

Skills

Generative AI concepts

Python

ML frameworks

LangChain

Vector databases

LLM APIs

Communication with students

Teaching assistant experience

Multi-agent AI concepts

Industry experience in AI/LLM

Education

Graduate-level course in Generative AI with grade A

Tools

PyTorch

TensorFlow

Hugging Face

LangChain

Vector databases

Job description

Posting Reason:

New Position

Location where work is to be performed:

Main Campus

Session:

2027 Winter Semester | Trimestre d’hiver

Faculty:

Faculté de génie / Faculty of Engineering

Unit:

School of Engineering Design and Teaching Innovation_ST

Job Classification:

Teaching Assistant/Demonstrator/Lab Monitor (CUPE)

Posting Type:

Cours précis / Specific course

Course Title:

Topics in Interdisciplinary Artificial Intelligence

Course Code:

MIA5150

Section:

D

Supervisor name (if known):

Wiam Ben Karroum

Date Posted (YYYY/MM/DD):

2026/10/28

Applications must be received BEFORE (YYYY/MM/DD):

2026/11/13

Description of tasks (hours):

Unless specified below, specific allocation of hours to various tasks should be articulated in a description of work negotiated and signed by you and the supervising professor prior to the commencement of work.

Recherche / Research:0

Préparation / Preparation:0

Contact avec étudiants / Contact with Students:65

Correction - Notation / Grading:55

Surveillance / Proctoring:10

Formation / Training:0

Autre / Other:0

Number of positions:

1

Expected Enrolment:

60

Work Start Date:

janvier 04, 2027

Work End Date:

avril 30, 2027

Total Work Hours:

130

Hourly Rate:

AE-RA-Tuteur / TA-RA-Tutor : $33.83 ou/or $53.31 (Sept. 2026 - Aug. 2027)

Undergraduate students will be paid at the lower rate; while graduate students will be paid at the higher rate.

These rates do not include vacation pay nor statutory pay.

Method of Delivery:

na

Language of Work:

Anglais | English

Requirements and Nature of Work:

• Completed an equivalent graduate-level course in Generative AI and LLMs (or a closely related course) with a grade of A or higher.
• Strong understanding of Generative AI and LLM concepts, including Transformers, prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and multimodal AI.
• Proficiency in Python and experience with modern AI/ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, and vector databases)
• Familiarity with LLM APIs and deployment frameworks
• Excellent communication with the ability to effectively support students during tutorials, labs, and office hours
• Assets
• Previous teaching assistant experience
• Familiarity with agentic AI concepts and multi-agent frameworks
• Relevant industry experience developing or applying Generative AI or LLM-based applications

Additional Information and/or Comments:

All University of Ottawa employees are required under provincial law to successfully complete all mandatory legislated training offered by the University. The list of training requirements may be modified by provincial law. If you are invited to continue the selection process, please notify us of any particular adaptive measures you might require. We may consult with the Health and Wellness sector of Human Resources, if needed. Any information you send us will be handled respectfully and in complete confidence.

The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact the academic unit to communicate the accommodation need.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.