Top Machine Learning Jobs in Toronto

This role focuses on conducting innovative pilot projects and implementing data strategies to drive quality performance and the adoption of digital solutions across the organization.

The Senior Technical Product Manager will lead product vision for the ML team, collaborating with various teams to enhance user experiences through ML tools and data solutions, tracking KPIs and project lifecycles.

The Machine Learning Engineer will build and deploy data products, collaborate cross-functionally, improve customer experiences, and mentor others in AI methods.

The Principal Data Scientist will lead analytics strategies, drive execution, mentor junior scientists, and innovate analytical practices for business decisions.

Manage the delivery of AI-powered agent assistance projects from design to deployment, including financials, risks, and stakeholder engagement.

As a Product Manager, you will develop customer-centric products leveraging technology, lead cross-functional teams, and define success metrics while fostering innovation and team culture.

Develop predictive models and apply machine learning to enhance Marketing strategies. Collaborate with teams to drive data-informed decisions and measure initiative impacts.

The Engagement Manager II oversees the deployment of AI solutions, leads workshops, manages customer relations, and drives process improvements in project execution.

As a Senior Engineering Manager for ML & AI, you'll lead Data Science and ML initiatives, mentoring team members, and collaborating across R&D to drive strategic AI solutions that impact the business.

As a PhD AI Research Intern, you'll collaborate with ML researchers to design experiments and evaluate AI models, contributing to publications while gaining practical experience in AI and machine learning applications.

Lead and manage a team of software engineers to develop innovative hardware, software, and AI solutions for physical operations, ensuring customer satisfaction and team growth.

The Principal Product Manager, AI will lead the AI platform strategy at Webflow, collaborating across teams to enhance product innovation and growth, and develop a unified AI strategy based on customer insights.

The AI Engineer will develop and optimize AI solutions, focusing on LLMs, manage datasets, and collaborate with cross-functional teams to align AI/ML solutions with business objectives while ensuring data quality and performance.

The Senior Lead AI Solutions Consultant at Braze drives revenue by enhancing the understanding of the BrazeAI tools, engaging with enterprise customers, leading workshops, and collaborating across teams to improve products and customer solutions.

The AI Business Analyst will optimize Dropbox's support systems using AI, analyze performance, and guide AI project prioritization to improve customer outcomes.

Lead teams in developing computer vision and machine learning solutions for AI dash cameras. Oversee model lifecycle and ensure reliable features by collaborating across teams.

Define and execute the product vision for leveraging data science at DraftKings, focusing on personalization and customer engagement through collaboration across multiple teams.

Lead engineering for agentic, domain-focused AI services, convert research into production-grade microservices, and optimize ML workflows and models.

The Director of Digital Technology for Snacking will drive the technology strategy and digital transformation within the Global Snacking division, emphasizing innovation and customer experience, and overseeing tech-related investments and implementations.

The role involves designing and refining AI/ML models, conducting R&D on architecture and safety, and implementing advanced analytics for financial services.

Lead the vision and development of Machine Learning capabilities at Affirm, managing model lifecycles and fostering AI adoption across products and teams.

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

The Sales Engineer will lead technical sales aspects, demonstrate AI capabilities, design solutions, and guide customer strategy for AI deployment.

Lead the development of AI-powered solutions for legal teams, driving product strategy and collaborating with cross-functional teams to enhance user experience.

Lead innovative technology solutions integrating AI, machine learning, and data governance into audit processes while mentoring teams and driving strategic initiatives.