Top Machine Learning Jobs in Toronto

Lead the Consumer Risk product for Affirm, focusing on Credit, Pricing, and Fraud, while managing a team of Product Managers and collaborating cross-functionally to drive product strategy and execution.

Lead the product strategy for personalization systems at CookUnity, collaborating with ML, engineering, and design teams to enhance user experience and drive retention through personalized food recommendations.

The Head of Design will lead design efforts for Square's Financial Suite, focusing on product experience, automation, and team mentorship while integrating financial management tools for small businesses.

The role involves leading the architecture and implementation of ML pricing models, building data pipelines, ensuring AI integration in production, and mentoring technical staff.

As a Senior Software Engineer, you'll automate and enhance business processes, mentor team members, and ensure high-quality system design across various backend applications.

Architect and develop software innovations for Quartus, focusing on optimization algorithms for FPGA tools, enhancing routing and retiming capabilities.

As an Account Executive, you'll manage the sales cycle for enterprise customers, design sales strategies, and collaborate with technical teams to drive revenue growth.

The Product Manager will oversee the global content lifecycle, implementing a self-service content management platform using Adobe Experience Manager and integrating AI capabilities.

Design and build AI-driven developer tools, integrate third-party AI models, mentor engineers, and improve AI coding agents to enhance software development processes.

As a Senior Machine Learning Engineer, you'll develop ML solutions, design APIs, maintain data pipelines, and collaborate with teams for optimal performance and innovation.

As a Senior Machine Learning Engineer, you will develop ML/AI applications, enhance operational safety and efficiency, and collaborate with various teams on innovative projects.

Develop and launch machine learning algorithms for Lyft's platform, collaborating with engineering and business teams to apply machine learning solutions. Responsible for building statistical and optimization models and evaluating their impact on business goals.

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

Lead exploration and development of Generative AI in AEC applications, collaborating with teams and managing project progress while addressing customer needs.

As a Machine Learning Engineer II, you will build advanced ML models and systems, collaborate with teams, and improve personalized experiences on Pinterest.

The Product Manager will lead AI systems development, manage product roadmaps, collaborate across teams, and use data to influence product strategies. Strong expertise in marketing technology and product delivery is required.

Lead the delivery of product capabilities in Risk and Controls domain, focusing on RCSA. Manage product backlogs, collaborate with teams, and drive continuous feedback and improvement within an Agile framework.

Lead sales efforts in the Insurance sector, driving customer acquisition and managing relationships to expand business. Collaborate with teams to close deals and mentor staff.

Oversee the Business Continuity Program, ensuring operational resilience, crisis management, and compliance with industry standards while leading communication and training efforts.

Lead the development of AI/ML systems for TIDAL, enhancing user experience through personalized recommendations and playlists while collaborating with cross-functional teams.

The Director of Machine Learning will lead a new ML team, managing strategies for Document Generation and AI systems while collaborating with Product and Engineering.

The Senior Manager of Machine Learning will lead a team to build and scale ML systems, ensuring they are production-ready and scalable, while collaborating with product and engineering teams.

Lead a multidisciplinary Agile team to develop data products, manage backlogs, and ensure alignment with customer needs and business objectives.

Lead data and AI transformation programs, partnering with executives to define strategies and deliver modern data platforms and solutions, while driving business growth and ensuring excellence.

Lead the development of AI agent solutions, manage a machine learning engineering team, and ensure project delivery and integration with Workday.