Top AI Jobs in Toronto

Lead data and AI transformation programs, build modern data platforms, and deliver solutions leveraging machine learning and AI for business growth.

Seeking a Data & AI Architect to design and implement enterprise-grade data and AI solutions, lead teams, and ensure architectural integrity.

The role involves managing AI and DevOps platform support, leading a professional team, ensuring platform reliability, and overseeing incident management and service improvements.

As an AI Native Staff Software Engineer, you'll design and manage AI workflows, set development standards, ensure observability of AI systems, and align teams on outcomes while focusing on operational excellence and embedding responsible AI.

As an AI Operations Developer, you will manage AI-driven projects, develop workflows, and support marketing automation to enhance team efficiency and effectiveness.

Lead the strategy and delivery of data and AI capabilities, ensuring scalable solutions while managing teams and stakeholder engagement.

The role involves leading the development of ML/AI systems, designing data pipelines, deploying ML models, and collaborating across teams to establish best practices.

As an Agentic AI Architect/Engineer, you'll lead AI solution architecture, optimizing ML systems, architecting AI pipelines, and managing CI/CD processes, while ensuring compliance and security in cloud environments.

The Senior AI Software Engineer will lead the development of AI-augmented applications, oversee full-stack development, define technical standards, integrate design and development processes, and mentor teams to enhance productivity.

As an Applied AI Engineer, you will design, develop, and deploy AI automation solutions, integrating LLMs into business workflows, and collaborating with stakeholders. Responsibilities include building reliable systems, supporting clients, and enhancing features.

Develop an AI Platform for efficient training and inference of large scale models, focusing on scheduling and resource management.

The role involves building AI inference systems, optimizing GPU performance, and developing benchmarking methodologies for large-scale deployments.

Assist in deploying and monitoring Cerebras AI infrastructure, perform troubleshooting, collect telemetry, and learn through shadowing senior engineers.

The Workplace AI Specialist trains staff on AI tools, develops prototypes, conducts needs assessments, and supports AI integration across departments.

The role involves leading AI driven test automation, ensuring quality application delivery, building test frameworks, and collaborating with teams in Agile environments.

The Director, Mainframe Innovation and AI at CIBC will lead strategy for innovation and automation in mainframe operations, managing a team and overseeing project delivery aligned with organizational goals.

The Applied AI Engineer will own full-stack feature delivery, build AI pipelines, integrate financial APIs, and work cross-functionally on new product builds in an autonomous role.

Participants will learn to design intelligent AI workflows and automation tools using modern AI technologies and publish their own projects within eight weeks.

The Manager, AI Enablement leads AI use-case delivery and architecture alignment, collaborating across teams to deliver scalable AI solutions in a cloud environment, focusing on MLOps and technical business needs.

Lead AI Engineer responsible for designing AI systems, implementing NLQ solutions, optimizing frameworks, and collaborating with cross-functional teams to deliver business outcomes.

The role involves managing marketing programs, overseeing AI-driven workflows, ensuring alignment with business objectives, and collaborating across teams to optimize resource usage and communication.

The Senior AI/ML Research Engineer will conduct advanced AI research, develop algorithms, mentor juniors, and publish findings while collaborating across teams to create innovative AI solutions.

The Solutions Architect will collaborate with customer teams to design tailored solutions, engage through implementation, and analyze customer feedback to drive continuous improvement.

Train large language models to improve code quality by ranking, repairing, and refactoring code snippets while providing detailed explanations for feedback.

The Software Engineer will train large language models to generate and improve code through ranking and editing. Responsibilities include repairing AI-generated code and providing detailed feedback for model refinement.