Top AI Jobs in Toronto

Lead design of foundational AI models, optimize training efficiency, analyze AI infrastructures, and collaborate with internal/external organizations to enhance algorithm performance.

The Senior Technical VP leads AI competitiveness planning, ensuring product performance and innovation in AI computing systems through hardware/software co-design.

As an Intern Researcher, you will develop AI agents powered by LLMs, prototype core capabilities, and explore new research directions while collaborating with experts.

The Co-op Researcher will work on embodied AI research, implement algorithms, collaborate with researchers, and write technical reports.

Lead system-level optimization of open-source AI frameworks, focusing on LLMs and reinforcement learning. Drive innovations and collaborate across teams.

Lead the design and development of AI-driven multimodal interaction systems, focusing on user experience, system integration, and innovative interaction models.

Lead the development of AI training cluster frameworks and optimization technologies, enhancing efficiency and performance for large model training scenarios.

The Principal Architect will design foundational model architecture for AI, optimize hardware efficiency, and lead distributed training infrastructures.

Research emerging trends in AI-powered big data systems, develop proofs-of-concept, optimize performance, and collaborate on innovative solutions.

Lead the design and deployment of AI multi-agent systems on cloud platforms, integrate AI models, and collaborate with a global team.

The Technical VP for AI & Data Storage will define technology roadmaps, lead research advancements, and mentor engineers in evolving storage systems integrated with AI.

The Co-op Researcher role involves investigating autonomous driving problems, designing algorithms, prototyping ideas, and collaborating with researchers in AI advancements.

Conduct applied research to develop AI data engine and storage architectures for large-scale workloads, optimize system software, and advance AI storage technologies.

The Researcher will design AI systems for scientific algorithm discovery, collaborate with teams, publish findings, and drive innovative research.

The role involves leading AI/ML technical planning, evaluating new technologies, collaborating with stakeholders, and fostering innovation in the team.

As an Intern Researcher, contribute to research on large language model-based agents, focusing on evaluation and autonomous reasoning. Involves formulating problems, conducting experiments, and contributing to publishable work.

The researcher will develop and evaluate AI/ML models, prototype innovative solutions, and collaborate to enhance product capabilities for smart devices.

Develop and implement AI risk assessment and pricing frameworks by evaluating AI models, creating rating tables and pricing models, collaborating with underwriters, building Python-based analytical tools, and researching emerging AI risks and mitigation strategies.

Conduct research into AI model behavior and failure modes; design and build models, agents, and automated evaluation pipelines to assess AI risk; develop production-grade tooling for continuous monitoring and model testing; create novel risk metrics; collaborate with underwriting and actuarial teams to translate findings into pricing signals; prototype and deploy robust, well-tested systems while communicating results to technical and non-technical stakeholders.

Design, build, and maintain adversarial AI evaluation platforms and AI pipelines. Implement software engineering best practices for ML, integrate UI/UX, deploy on major cloud providers, and collaborate cross-functionally to improve model robustness and product infrastructure.

Lead the design of generative AI solutions and multi-cloud architectures, translating business use-cases into scalable systems for enterprise deployments.

The Associate AI Engineer will assist in building AI-powered backend services, integrating APIs, and developing data pipelines while collaborating with experienced engineers and teams.

Lead client engagements and own end-to-end solutions, prototyping while ensuring reliability and scalability. Mentor engineers and help define technical roadmap.

The AI Architect will design, code, and deploy hands-on AI solutions, leveraging AWS and Agentic AI patterns while leading technical team growth.

The AI Product Manager will lead the development of AI-powered applications, collaborating with engineers and designers to align AI technologies with user needs and business objectives.