Top AI Jobs in Toronto

The Applied AI Specialist will design and implement AI features, develop APIs, optimize workflows, and manage deployment of machine learning models.

The Applied AI Specialist will design and maintain data pipelines for ML, prepare datasets, collaborate with AI engineers, and ensure data reliability for AI applications.

Design, build, and iterate on fullstack systems for AI agents. Collaborate with teams to enhance UX and contribute to internal best practices while engaging in research related to AI technologies.

Lead the design, development, and delivery of enterprise data engineering solutions while managing project timelines and fostering knowledge sharing in data engineering practices.

Lead strategic initiatives for Project & Pipeline Analytics and External Data Solutions. Oversee product development and manage teams to enhance AI-driven decision-making in R&D.

The Senior Software Engineer will lead the technical roadmap for AI initiatives, architect LLM systems, and mentor engineers while collaborating with product teams to design technical solutions.

Develop and optimize AI/ML models using Python, implement prompt engineering and RAG strategies, and collaborate with teams to integrate AI solutions.

Lead the development of AI-powered solutions, drive technical strategy and innovation, mentor engineers, and ensure quality and operational excellence.

Responsible for bridging enterprise data with AI capabilities, translating business challenges into operational solutions, and driving complex sales deals by connecting technical solutions to business value.

Train large-language models (LLMs) by evaluating, ranking, repairing, and refactoring code. Provide detailed feedback and maintain the RLHF pipeline.

The Software Engineer will analyze, rank, and improve AI-generated code, providing feedback for reinforcement learning in a remote role.

The role involves training large-language models to improve code generation, reviewing and editing AI-generated code, and providing feedback for reinforcement learning refinement.

Seeking senior technology leaders for advisory roles on AI product decisions, requiring expertise in AI/ML at scale, system design, and producing decision-ready artifacts.

As a Product Design Intern, you'll design user experiences for AI Agent products, conduct user research, prototype, and collaborate with teams to enhance product strategy and usability.

The Data/AI Engineer will architect AI applications, manage the AI application lifecycle, optimize RAG pipelines, and mentor junior engineers, leveraging technologies like Python and Azure.

Lead the design and deployment of AI/ML solutions for grid automation, manage teams, drive innovation, and ensure adherence to architectural standards.

The Senior Application Engineer will architect and develop AI agents using Salesforce Agentforce, build automations, and integrate external data sources, while collaborating on projects and mentoring others.

Lead the development of AI agents and their platform, including LLM training, backend infrastructure, and technical leadership across teams.

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

Design and operate cloud infrastructure for analytics and machine learning, ensuring governance and compliance while providing mentorship and collaboration across teams.

This internship involves supporting demand generation through campaign execution, using AI and analytics to derive insights, and optimizing workflows for marketing processes.

As a Senior Data Scientist, you will design and build AI and machine learning models, collaborate with teams, and drive analytics strategy for business value.

The Staff Software Engineer will lead the technical strategy for AI platform development, architect foundational AI systems, ensure alignment between teams, and mentor engineers while driving organizational engineering standards.

The AI Training & Enablement Lead is responsible for designing and delivering AI training programs, managing user enablement, and driving adoption of AI tools across the organization. This includes creating materials, conducting training sessions, and overseeing feedback and improvement processes.

The AI Enablement & Engagement Lead drives AI adoption in business units, facilitates workshops, manages relationships, curates documentation, and tracks AI solution usage.