Top AI Jobs in Toronto

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

As a Senior Software Engineer, you will develop AI agent applications, focusing on performance, integration with systems, and mentorship of junior engineers.

Design and build scalable backend services and APIs, develop distributed systems for AI integration, ensure system reliability, and collaborate cross-functionally.

Develop user-facing products and features using modern technologies, collaborating with design and back-end teams to solve complex challenges.

The AI Enablement Operations Lead coordinates logistics for workshops, manages connections between stakeholders, and transforms processes into scalable systems for high-impact engagements.

Lead and scale AI and Machine Learning initiatives, architect frameworks, manage budgets, oversee engineering teams, and drive innovation in AI solutions.

Lead the design and implementation of a scalable AI insights engine, build robust Python APIs (Django, FastAPI), develop ML/AI-adjacent systems (RAG, workflows, evals), ensure platform reliability and scalability, and manage a small engineering team while working directly with customers to close capability gaps.

Manage and mentor an engineering team to develop AI integrations and multimodal user experiences for Lyft. Drive technical strategy and ensure timely delivery of high-quality solutions.

The Principal AI Developer will design and implement AI features, drive code reviews, troubleshoot issues, and contribute to technical roadmaps, focusing on scalability and performance for a reliable platform.

Manage developer-facing initiatives in generative AI, oversee internal tools, deliver external APIs, identify new AI opportunities, and ensure compliance with responsible AI principles.

The AI Quality Assurance Intern will evaluate AI systems' behavior and accuracy, ensuring they perform as intended and meet business logic requirements.

The Revenue Operations Manager will drive data-informed decisions, enhance forecasting and pipeline management, and optimize processes using advanced analytics and AI initiatives.

As an AI-First Account Executive, you will manage the full sales lifecycle, using AI for prospecting and engaging clients, while innovating workflows and maintaining high-quality partnerships.

The Senior Product Manager will lead AI product strategy, define AI capabilities, collaborate with engineering, and drive impactful outcomes for customers.

As an AI Research Engineer, you'll implement image and video generation models, manage training pipelines, and optimize performance while collaborating with researchers.

As a Software Engineer, you will develop features for SaaS products, collaborate on technical designs, write clean code, and troubleshoot production issues.

As an AI Engineer, you will design and deploy scalable AI solutions, optimize models, integrate AI into enterprise environments, and monitor production AI systems while collaborating with various teams.

The Sales Strategy and Operations Manager leads complex sales opportunities, develops ROI models, engages executives, and coordinates cross-functional input for compelling proposals.

This role involves leading enterprise clients in enhancing their Microsoft 365 collaboration using AI technologies, while also ensuring security and compliance. The consultant will architect, implement, and govern solutions such as SharePoint Online and manage AI integration.

The role involves designing and implementing AI features, building APIs, participating in code reviews, and ensuring software scalability and reliability.

The AI Engineer will design, develop, and deploy ML models, collaborate with teams to integrate AI into applications, and optimize model performance.

The AI Resilience Fund Manager will establish a fund focused on resilient investments against AI disruption, lead capital raising, and advise investors on long-term strategies.

Design and build conversational AI agents for customer service, ownership of agent systems from architecture to production, and implement safety and evaluation frameworks.

Lead the definition and rollout of AI-powered product features, collaborating with teams to enhance fraud prevention solutions.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.