Top AI Jobs in Toronto

As a Machine Learning Engineer, you'll develop scalable ML solutions using Google Cloud Platform and Vertex AI, collaborate with teams, and operationalize models from ingestion to monitoring.

The Agentic AI Lead/Architect will define AI architecture on Azure, lead design of AI automation use cases, and mentor engineers.

Lead operational rhythms and client delivery, focusing on AI solutions. Collaborate with executives and manage multi-stakeholder projects for positive outcomes.

As a Staff Product Designer, you'll shape AI-focused designs for HubSpot's product line, influence product strategy, and create prototypes that enhance customer experiences across various platforms.

Drive technical sales and customer success for AI companies, owning implementation and providing effective solutions for usage-based billing.

The GTM Operations Specialist is focused on deploying AI-driven GTM content, managing asset creation, and optimizing workflows for team efficiency. Responsibilities include project management, content readiness for events, and cross-functional collaboration to meet timelines and metrics for product launches.

The AI Ethics Advisor will develop ethical frameworks, provide guidance on responsible AI technologies, design training programs, and assess societal impacts, ensuring alignment with robust ethical principles.

As an ESG & CSR Responsible AI Intern, you'll develop AI ethics principles, collaborate with teams, conduct audits and promote transparency in AI practices.

As a Senior Software Engineer, you will develop AI-powered systems to enhance accounting workflows, build backend services, and ensure optimal performance and reliability of AI solutions.

The Generative AI Developer will design, deploy, and manage generative AI systems in an enterprise setting, collaborating with engineers and architects to ensure solutions are scalable, secure, and compliant with governance standards.

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

As an AI Application Engineer, build and deploy Agentic AI applications for Fortune 500 companies, analyze customer requirements, and enhance the GenAI performance.

Build and maintain scalable backend services and APIs, optimize system performance, collaborate with stakeholders, and improve AI workflows.

Build and deploy high-impact AI-native products, architect agent-driven workflows, and collaborate with teams to integrate cutting-edge AI solutions into production systems.

As AI Resilience Fund Manager, you'll establish and manage a fund focused on resilient investments, lead fundraising, and advise investors on navigating challenges created by AI and economic shifts.

Design, deploy, and improve endpoint systems with an automation-first mindset, using AI-driven tools for enhanced security and operational efficiency.

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

The Product Marketing Manager will own go-to-market strategies and lead product launch planning while collaborating with teams to enhance marketing assets and support customer education.

The Software Developer for Generative AI will design and deploy applications using Large Language Models, collaborate with teams, optimize LLM applications, and manage the full product lifecycle.

The role involves applying diffusion techniques and developing AI models to enhance 3D reconstruction pipelines for various industries.

The Technical Program Manager will lead AI/ML program execution, manage LLM infrastructure, oversee implementation of AI solutions, and drive project delivery, ensuring alignment with business goals and client engagement.

The AI Engineer role involves optimizing language models for fraud detection and building backend infrastructure to support scalable operations for risk management and as well as developing efficient machine learning solutions.

Lead sales efforts for AI solutions at Labelbox, developing relationships with top AI labs and Fortune 500 companies, managing the sales cycle and ensuring client satisfaction.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.