TA (CUPE) - MIA5150 D - Winter 2027
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Before you apply
SalaryCA$34 – CA$53/hr
LocationOttawa, ON; Main Campus
Work modeon-site
Typeinternship
SeniorityEntry
DepartmentFaculty of Engineering
Company size10,000+ people
PostedOct 28, 2026 · 1w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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
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
All University of Ottawa employees are required under provincial law to successfully complete all mandatory legislated training offered by the University
The University embraces diversity and inclusion and encourages applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons
Skills
Python
PyTorch
TensorFlow
Hugging Face
LangChain
Vector databases
LLM APIs
Generative AI
Transformers
RAG
Fine-tuning
Multimodal AI
Agentic AI
Multi-agent frameworks
Benefits
Diversity and inclusion
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
Hiring process
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 :0Préparation / Preparation :0Contact avec étudiants / Contact with Students :65Correction - Notation / Grading :55Surveillance / Proctoring :10Formation / Training :0Autre / 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:
Legal
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 hiring process will be governed by the current CUPE 2626 collective agreement; you can click here to find out more.
About the company
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.