Top Machine Learning Jobs in Toronto

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.

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.

Analyze large data sets to identify trends and fraudulent behaviors, collaborating across teams to drive risk management innovations.

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.

Lead the transformation of finance technology, focusing on architecture, strategy, and innovative AI-driven solutions to optimize financial processes.

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

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

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.

Lead and mentor a team of fraud analysts to identify and mitigate fraudulent activity. Collaborate with cross-functional teams to improve fraud detection processes and develop ML models for risk management.

As Product Lead, you'll enhance dispute resolution for Cash App, leading cross-functional teams to improve customer trust, compliance, and operational efficiency.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

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.

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

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.

Lead the design vision for Square's Financial Suite, managing design teams, driving design quality, and enhancing user experience through innovative financial tools.

The Head of AI leads the design and implementation of AI initiatives, focusing on enhancing operations and customer experience. Responsibilities include strategy development, team management, product development, and compliance oversight.

Lead the BNPL product strategy focusing on inclusion and transparency in credit systems. Collaborate across teams to build a seamless user experience and ensure regulatory compliance.

Lead and develop the Data Loss Prevention Team, establishing strategy and overseeing implementation of DLP tools to enhance security and efficiency at Coinbase.

As a Staff Machine Learning Engineer at Coinbase, you will define technical strategies, design ML models for risk assessment, create real-time ML pipelines, and deploy models at scale to optimize operations and enhance user security.

Lead the Payments Risk engineering team at Coinbase, develop strategies, mentor team members, ensure code quality, and collaborate with cross-functional teams to manage financial risks.

Lead and develop a team to investigate and mitigate fraud risks, collaborating with various departments to improve controls and processes. Drive innovation in risk management through analytical skills and machine learning model enhancement.