Top AI Jobs in Toronto

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.

The intern will research and prototype AI agents and intelligent systems, analyze industry trends, develop experimental AI applications, and contribute to internal reports on emerging AI technologies.

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

Conduct advanced research and prototyping in speech/audio AI, design deep learning architectures, develop audio AI capabilities, and collaborate with teams on innovative intelligent products.

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

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

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 Business Development Manager will drive sales growth for the Revenue Insight platform in the Asia-Pacific region, focusing on client acquisition, relationship management, and strategic market planning in the hospitality sector.

The AI Developer II role involves delivering AI and machine learning solutions, integrating into teams, and evolving AI software products across various projects.

The role involves developing innovative machine learning solutions, transforming datasets into insights, maintaining data tools, and collaborating across departments to promote data-driven decision-making.

Design, develop and optimize microservices, APIs and reusable libraries to run ML algorithms in production. Improve platform scalability, testability and team velocity; mentor squad members; collaborate on task prioritization, DevOps, component/integration testing, and quality assurance.

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 strategy, governance, and execution for enterprise business applications (notably Dayforce), integrations, AI/automation initiatives, and application support. Drive roadmap, vendor management, acquisition-related system integration, cross-functional delivery with HR/Finance/Operations, and build a high-performing applications team to enable digital transformation and operational efficiency.

Lead the full development lifecycle, building scalable APIs and systems, mentoring engineers, and delivering impactful AI-driven software solutions.

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

Lead a team of up to 12 engineers to build and operate critical parts of an AI-native healthcare automation platform. Drive technical execution, architecture, reliability, incident response, hiring, onboarding, and cross-functional execution while ensuring enterprise security, compliance, and scalable customer deployments.

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.

As an AI/ML Engineer, you'll develop and optimize machine learning models for mobile applications, collaborate with teams, and integrate AI-driven features to enhance user experience.