Machine Learning Associate

Machine Learning Associate Data / ML Internship# Machine Learning Associate at Vector Institute
** Location
* * Toronto, Ontario Hybrid
** Details
* * Co-op
· 4mo · $25/hr
· Aug 2026 - Dec 2026
** Posted
* * Jun 01, 2026

Apply on company site →Direct apply link, refreshed by the daily generator.## About the Role Design and deploy AI proof-of-concept solutions## About Vector Institute Canada's leading AI research institute## Full Description Machine Learning Associate (MLA)
** Position Overview
** The Vector Institute is seeking Machine Learning Associates (MLAs) to join the Fast Lane MLA Program. In this role, MLAs will be matched with Canadian small- and medium-sized enterprises (SMEs) to work on applied projects focused on Generative AI and Agentic AI. Working in teams of two to three individuals, MLAs will design, develop, and deliver proof-of-concept AI solutions that address real-world business challenges.

This position may be remote, hybrid, or onsite, and offered in either full-time (36.25 hours/week) or part-time (20 hours/week) formats. Specific work arrangements will be discussed during the interview based on company requirements and MLA availability. MLAs will receive technical mentorship and structured support from Vector’s Technical Advisors and Project Specialists throughout the project cycle.

Start date:

August 24, 2026

End date:
December 11, 2026

FASTLANE MLA PROGRAM AT VECTORThe Fast Lane MLA Program is a four-month, cohort-based initiative led by the Vector Institute and designed to support the career growth of early-stage AI professionals while accelerating AI adoption in Canada’s small- and medium-sized enterprises (SMEs). The program connects graduate-level AI talent with innovative companies to deliver applied AI solutions that create real business value.
** Key Responsibilities
** Understand Business Case
* Work with the company and MLAs to frame the AI problem based on business needs;
* Research and design effective AI solutions aligned with the company’s business goals, data readiness, and infrastructure constraints; and,
* Break down complex problems into minimal milestones and develop a project plan that ensures value delivery within the project timeline.

Develop Proof-of-Concept (POC)
* Preprocess data to meet the quality and format needs of the AI model or pipeline;
* Develop, test, and evaluate models and pipelines to deliver robust, scalable AI solutions;
* Deploy AI solutions on company-provided infrastructure, such as GCP, AWS, or Azure;
* Refine and optimize the AI solution through iterative experimentation; and,
* Rapidly design, develop, and deliver AI solutions tailored to the company’s use case.

Deliver Business Value
* Engage in regular touchpoints with Vector and the company to align with business needs;
* Utilize learning sessions and office hours to transfer knowledge and support the company’s AI adoption efforts;
* Create project documentation, including a Showcase Day presentation, and Final Report;
* Ensure seamless handover to the company through clear and well-documented deliverables; and,
* Perform other duties as required to ensure project success.

PROFILE OF THE IDEAL CANDIDATE
* You are a student or recent graduate of an AI-focused Master’s or PhD program in Canada, or conducting research under the supervision of a Vector Institute Faculty Member.
* You have completed at least one machine learning project involving design, development, and deployment in either an academic or professional setting.
* You are proficient in Python programming.
* You have knowledge of AI techniques related to Generative AI and Agentic AI, such as prompt engineering, fine-tuning, autonomous agents, memory and tools integration.
* You have hands-on experience with leading ML frameworks and tools commonly used in multimodal AI and agentic workflows, such as Tensor Flow, PyTorch, OpenAI APIs or equivalent, Transformers library, Lang Chain, and Streamlit or Gradio.
* You have prior experience deploying AI solutions in real-world or production environments.
* Experience with LLM application frameworks, backend deployment (e.g., FastAPI), and cloud platforms (AWS, GCP, or Azure) is an asset.
* You are…