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Generative Ai Developer Jobs in Ontario (NOW HIRING)

Generative AI EngineerAbout Apertera Apertera is leading the evolution of language solutions for ... Work closely with software and DevOps engineers to deploy GenAI models. * Document code, algorithms ...

AI Engineer

Toronto, ON ยท On-site

Explore and apply cutting-edge Generative AI methodologies, including prompt engineering, agents, model adaptation, and deployment strategies, to enhance the effectiveness of AI-driven solutions.

AI Developer/Prompt Engineer

Toronto, ON ยท Hybrid

CA$100K - CA$140K/yr

The AI Developer lead the design, development, and deployment of advanced AI-enabled solutions in ... Architect, develop, and deploy production-grade AI and generative AI solutions aligned with ...

With over 1,600 professionals dedicated to generative AI, leveraging the depth and experience of ... As an Advanced AI, Large Language Model and Agentic AI Developer/Consultant, you will build ...

AI Engineer

Kitchener, ON ยท On-site

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 ...

AI Engineer

Markham, ON ยท On-site

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 ...

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 ...

AI Engineer

Guelph, 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 ...

The AI Engineer is an individual contributor responsible for designing, building, and ... Generative AI & Advanced AI Capabilities * Implementation of Generative AI patterns such as ...

Vice President, AI Engineer

Toronto, ON ยท On-site

CA$120K - CA$150K/yr

In this role, you will design, develop, and deploy advanced AI solutions with a focus on Agentic AI, Generative AI, and Large Language Models (LLMs). You will work on applied science and engineering ...

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 ...

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 ...

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Generative Ai Developer information

What are some common challenges faced by Generative AI Developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a Generative AI Developer, and why are they important?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

Is generative AI a good career?

Generative AI is a rapidly growing field with high demand for skilled developers who can create and optimize AI models using tools like deep learning frameworks. Careers in this area often require knowledge of machine learning, programming, and data handling, offering opportunities in tech companies, research, and startups. The field provides competitive salaries and continuous learning opportunities due to its evolving nature.

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

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is the salary of a generative AI developer?

The salary of a generative AI developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill set. Senior developers with expertise in machine learning frameworks and deep learning may earn higher compensation, especially in tech hubs or companies with advanced AI projects.

What does a generative AI developer do?

A generative AI developer designs and builds algorithms that enable machines to create content such as text, images, or audio. They work with machine learning frameworks, train models on large datasets, and optimize algorithms for performance and accuracy, often using tools like Python and TensorFlow or PyTorch.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence development, such as a senior Generative AI Developer or AI research lead, often involving advanced skills in machine learning, deep learning, and large language models. These roles usually require extensive experience, specialized knowledge, and may include responsibilities like designing AI systems, managing teams, or overseeing AI strategy in organizations with competitive compensation packages. Such salaries are common in top tech companies or specialized AI firms for highly skilled professionals.

What is a Generative AI Developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.
What are popular job titles related to Generative Ai Developer jobs in Ontario? For Generative Ai Developer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Generative Ai Developer jobs in Ontario look for? The top searched job categories for Generative Ai Developer jobs in Ontario are:
Infographic showing various Generative Ai Developer job openings in Ontario as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution.

Generative AI Engineer

Apertera

Toronto, ON โ€ข On-site

Full-time

Posted 2 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:ย 

  • 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.ย ย ย ย 
  • 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 Masterโ€™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.ย 
  • Expert skills of Python, including PyTorch, TensorFlow, Pandas, etc.
  • Experience with cloud platforms like AWS, GCP, or Azureย 
  • 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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