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Computer Science Artificial Intelligence Jobs in Ontario

Royal Bank of Canada

Lead AI/ML Scientist

Toronto, ON · On-site

PhD or Master's degree (or similar) in computer science, statistics, AI/machine learning, physics ... Artificial Intelligence Technologies, Big Data Management, Data Mining, Data Science, Decision ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

... artificial intelligence algorithms for our self-driving vehicles. You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and ...

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Computer Science Artificial Intelligence information

Can I get an artificial intelligence job with a computer science degree?

A computer science degree provides a strong foundation for artificial intelligence (AI) roles, which often require knowledge of programming languages like Python, machine learning algorithms, and data analysis. Many AI jobs also value practical experience, internships, and familiarity with tools such as TensorFlow or PyTorch.

What computer science artificial intelligence jobs are in high demand?

High-demand artificial intelligence jobs in computer science include AI engineer, machine learning engineer, data scientist, and research scientist. These roles often require skills in programming languages like Python, knowledge of deep learning frameworks, and experience with large datasets, with industries such as tech, finance, healthcare, and autonomous vehicles actively hiring for these positions.

What does a typical day look like for someone working in computer science artificial intelligence?

A typical day in a Computer Science Artificial Intelligence role often involves researching and developing new models, collaborating with data scientists and software engineers, and testing or optimizing machine learning algorithms. You may spend a significant amount of time analyzing datasets, building prototypes, and reviewing code, as well as meeting with multidisciplinary teams to align on project goals. The role is dynamic, with a mixture of individual problem-solving and group brainstorming to tackle complex challenges. This variety ensures continual learning and hands-on interaction with the latest technological advancements in artificial intelligence.

What are the key skills and qualifications needed to thrive in computer science artificial intelligence, and why are they important?

To thrive in a Computer Science Artificial Intelligence role, you need strong programming skills (Python, Java, or C++), a solid understanding of machine learning algorithms, and typically at least a bachelor's degree in computer science or related fields. Hands-on experience with frameworks and tools like TensorFlow, PyTorch, Scikit-learn, and familiarity with cloud platforms is highly desirable, and certifications such as AWS Certified Machine Learning can be advantageous. Analytical thinking, problem-solving, teamwork, and effective communication are important soft skills for success in both independent and collaborative settings. These skills and qualifications enable professionals to design, implement, and deploy AI solutions that address real-world business challenges.

What is a computer science artificial intelligence?

A Computer Science Artificial Intelligence (AI) job involves developing, implementing, and improving AI technologies using machine learning, deep learning, and data analysis techniques. Professionals in this field work on algorithms, automation, and intelligent systems that can solve complex problems across industries like healthcare, finance, and robotics. Roles may include AI engineer, data scientist, or machine learning specialist, requiring strong programming skills in languages like Python and knowledge of AI frameworks.

What are the most commonly searched types of Computer Science Artificial Intelligence jobs in Ontario? The most popular types of Computer Science Artificial Intelligence jobs in Ontario are:
What are popular job titles related to Computer Science Artificial Intelligence jobs in Ontario? For Computer Science Artificial Intelligence jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Computer Science Artificial Intelligence jobs in Ontario look for? The top searched job categories for Computer Science Artificial Intelligence jobs in Ontario are:
What cities in Ontario are hiring for Computer Science Artificial Intelligence jobs? Cities in Ontario with the most Computer Science Artificial Intelligence job openings:
Computer Science Artificial Intelligence jobs near you
Infographic showing various Computer Science Artificial Intelligence job openings in Ontario as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Director of AI Engineering - Generative AI & Autonomous Systems (10033) Toronto, Canada

Extreme Networks

Toronto, ON • On-site

Full-time

Re-posted 22 days ago

Job description

Introduction 
At our Extreme, we create effortless networking experiences that empower people and organizations to advance. We are seeking a Director of AI Engineering to lead the design, development, and delivery of our next-generation AI-native systems. 
This role requires a proven leader who combines technical depth with organizational vision. You will not only set the direction for AI strategy but also ensure that ideas move from research to scalable, production-ready deployments. Your leadership will drive the successful launch of enterprise-grade AI solutions that transform network design, optimization, security, and support. 
Key Responsibilities
  •  
Leadership & Vision 
  • Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes. 
  • Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution. 
  • Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization. 
  • Champion responsible AI practices and set quality standards for reliability, ethics, and compliance. 
 
End-to-End Productization 
 
  • Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches. 
  • Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery. 
  • Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production. 
  • Measure impact and ensure that AI solutions deliver tangible business value. 
 
Technical Leadership 
 
  • Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models. 
  • Guide technical decisions, ensuring systems are reliable, secure, and cloud-native. 
  • Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation. 
  • Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership. 
 
Cross-Functional & External Influence 
 
  • Partner with product management, engineering, and network experts to define and deliver AI-driven features. 
  • Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence. 
  • Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements. 
Qualifications
  • A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience). 
  • Proven leadership track record: 12+ years in AI/ML engineering, including 5+ years in senior leadership roles managing teams and large-scale initiatives. 
  • End-to-end product launch expertise: Demonstrated success leading AI initiatives from concept through production deployment and adoption at enterprise scale. 
  • Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes. 
  • Team builder & mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence. 
  • Technical credibility: Strong foundation in ML/AI with applied expertise in generative AI, LLMs, RAG, or multi-agent systems; able to guide architecture and evaluate tradeoffs. 
  • Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP). 
  • Influence & communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact. 
Nice to Have:
  • Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management. 
  • Domain knowledge in networking, SD-WAN, or observability. 
  • Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership). 
  • Partnerships with academia, startups, or AI vendors to accelerate innovation. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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