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Generative Ai Engineer Intern Jobs in Toronto, ON

Apertera

Generative AI Engineer

Toronto, ON · On-site

We expect our Generative AI Engineer to to work at the intersection of LLM engineering, machine translation, cloud infrastructure, and evaluation. You'll play a pivotal role in pushing the boundaries ...

ShyftLabs

AI Engineer Intern

Toronto, ON · Hybrid

CA$20 - CA$30/hr

We are looking for an AI Engineer Intern interested in building production-ready AI agents and applications. You will contribute to the Continuum platform while also using it to build agentic ...

Royal Bank of Canada

AI Engineer

Toronto, ON · Hybrid

Embed Generative AI tools into Sales platforms, enabling seamless workflows for prospect research ... Programming Language), Retrieval-Augmented Generation, Software Development Life Cycle (SDLC ...

GEI Consultants

AI Engineer

Markham, ON

CA$110K - CA$150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

GEI Consultants

AI Engineer

Concord, ON

CA$110K - CA$150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Guidepoint

AI Engineer

Toronto, ON · On-site

You will develop and scale Generative AI-powered systems, including large language model (LLM ... The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using ...

Tiger Analytics Inc.

Gen AI Engineer

Toronto, ON · On-site

Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers. * Infrastructure & DevOps: Experience with DevOps, CI/CD pipelines, and ML ...

Tiger Analytics Inc.

Gen AI Engineer

Toronto, ON · Remote

Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers. * Infrastructure & DevOps: Experience with DevOps, CI/CD pipelines, and ML ...

iManage

Senior AI Engineer

Toronto, ON · On-site

... our generative AI document assistant, as well as document classification, extraction, and LLM ... Applying modern engineering practices for production AI systems, including containerized services ...

Levio

ML/AI Engineer

Toronto, ON · On-site +1

CA$110K - CA$150K/yr

The ML / AI Engineer design, build, deploy, and operate production-grade machine learning and generative AI systems. This role owns the end-to-end ML lifecycle, ensuring models and AI services are ...

Guidepoint

Senior Data/AI Engineer

Toronto, ON

You will develop and scale Generative AI-powered systems, including large language model (LLM ... The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities ...

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Generative Ai Engineer Intern information

What does a generative AI engineer intern do?

A Generative AI Engineer Intern assists in developing and testing machine learning models, specifically those that can create new content such as text, images, or audio. They work with frameworks like TensorFlow or PyTorch, collaborate with senior engineers, and help improve the performance and reliability of generative AI systems. Interns may also be involved in data preprocessing, model evaluation, and keeping up with the latest research in artificial intelligence.

What skills and qualifications are needed to thrive as a generative AI engineer intern?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, programming skills (especially in Python), and coursework or experience in artificial intelligence or computer science. Familiarity with deep learning frameworks like TensorFlow or PyTorch and version control systems such as Git is typically required, and relevant coursework or certifications in AI/ML are advantageous. Strong problem-solving skills, curiosity, and the ability to communicate complex ideas clearly help interns stand out. These skills and qualities are crucial for quickly learning advanced AI techniques, contributing to team projects, and driving innovation in a rapidly evolving field.

What types of projects can a generative AI engineer intern expect to work on during their internship?

As a Generative AI Engineer Intern, you can expect to work on projects involving the development, training, and evaluation of generative models such as GANs, VAEs, or transformer-based architectures. Typical tasks may include data preprocessing, model implementation, fine-tuning, and running experiments to improve model performance. Interns often collaborate closely with data scientists, software engineers, and research teams, gaining exposure to both research and application of AI in real-world products. This role provides hands-on experience with state-of-the-art tools and frameworks, offering a valuable foundation for a future career in AI engineering or research.

What is the difference between Generative Ai Engineer Intern vs Machine Learning Engineer Intern?

AspectGenerative Ai Engineer InternMachine Learning Engineer Intern
Required CredentialsBasic knowledge of AI, programming, and some coursework in machine learning or AIStrong foundation in machine learning, programming, and data analysis, often with coursework or certifications
Work EnvironmentTech companies, startups, research labs focusing on AI applicationsTech firms, research institutions, and companies applying machine learning models
Industry UsageDeveloping generative models like GPT, DALL·E, and similar AI toolsBuilding predictive models, data pipelines, and machine learning algorithms

While both roles involve AI and machine learning, a Generative Ai Engineer Intern focuses specifically on creating generative models like text, images, or audio, whereas a Machine Learning Engineer Intern works broadly on developing and deploying various machine learning algorithms across different applications.

What are the most commonly searched types of Generative Ai Engineer jobs in Toronto, ON? The most popular types of Generative Ai Engineer jobs in Toronto, ON are:
What are popular job titles related to Generative Ai Engineer Intern jobs in Toronto, ON? For Generative Ai Engineer Intern jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Generative Ai Engineer Intern jobs in Toronto, ON look for? The top searched job categories for Generative Ai Engineer Intern jobs in Toronto, ON are:
Generative Ai Engineer Intern jobs near you
Infographic showing various Generative Ai Engineer Intern job openings in Toronto, ON as of August 2026, with employment types broken down into 71% Full Time, 26% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Generative AI Engineer

Apertera

Toronto, ON • On-site

Full-time

Re-posted 18 days ago

Job description

Generative AI EngineerAbout Apertera

Apertera is leading the evolution of language solutions for high-stakes content. We partner with enterprises as an extension of their teams, combining professional expertise with Adaptive AI technology that is continuously refined by client context.

For more than twenty years, Apertera has set the bar for legal, financial, and regulatory translation, serving the most rigorous buyers, including over 75% of major national Canadian law firms, all major banks, and leading securities regulators.
Apertera is Canadian-owned, ISO 17100 and SOC 2 certified.

Our core values: 

  • Innovation
  • Dedication
  • Fanatical commitment to quality and service
  • Resourcefulness
  • Collaboration
About the Role

We are looking for a Generative AI Engineer to develop our next-generation intelligent translation and translation-related service engine, using Generative AI (GenAI) and Large Language Model (LLM) technologies. You will report to the team lead in AI Innovation, develop and implement state-of-the-art algorithms by fast prototyping, and collaborate with the software team to deploy models. We expect our Generative AI Engineer to to work at the intersection of LLM engineering, machine translation, cloud infrastructure, and evaluation. You'll play a pivotal role in pushing the boundaries of applying GenAI to translation scenarios and create innovative solutions.

Responsibilities
  • Implement state-of-the-art LLM techniques including continued pre-training, instruction fine-tuning, preference alignment, and LLM deployment.
  • Work closely with machine learning engineers and data engineers to design, build, and test models.
  • Develop efficient and scalable algorithms for training and inference of generative models, leveraging deep learning frameworks such as TensorFlow or PyTorch and optimizing performance on diverse hardware platforms.
  • Train and evaluate generative models using appropriate metrics and benchmarks, fine-tuning model parameters, architectures, and hyperparameters to optimize performance, stability, and generalization.
  • Built end-to-end prototypes that are production ready.
  • Work closely with software and DevOps engineers to deploy GenAI models.    
  • Document code, algorithms, and experimental results, following best practices for reproducibility, version control, and software engineering, and contributing to internal knowledge sharing and continuous improvement initiatives.
Requirements
  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields. A Master’s degree is preferred.
  • 2+ years of industry experience developing GenAI and LLM applications is preferred.
  • Proficiency in Python programming and software development practices, with experience in building and maintaining scalable, production-grade software systems.
  • Working knowledge and project-based record of all of the following: context engineering, RAG, harness engineering.
  • Working knowledge and project-based record of at least one of the following is a plus: LLM post-training, APO, agentic workflow.
  • Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively in a fast-paced environment.
  • Hands-on experience with Huggingface APIs or Amazon Bedrock. 
  • Expert skills of Python, including PyTorch, TensorFlow, Pandas, etc.
  • Experience with cloud platforms like AWS, GCP, or Azure 
  • Excellent problem-solving skills, critical thinking, and the ability to work independently and collaboratively in a fast-paced environment.
  • Strong communication skills, with the ability to articulate complex technical concepts effectively and work cross-functionally with diverse teams.
  • Self-driven, self-motivated with excellent time management skills
  • Excellent organizational, communication, and interpersonal skills
  • Ability to adapt to shifting priorities without compromising deadlines and momentum.

 

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