Top Machine Learning Jobs in Toronto

The Machine Learning Intern will design and train models, develop AI agents, and work with teams to create impactful applications.

Manage product strategy for search and embedding models, focusing on performance, user needs, and market competitiveness while collaborating with cross-functional teams.

As a Machine Learning Engineering Intern at Cresta, you'll design, develop, and deploy AI Agent solutions, collaborating across teams to implement cutting-edge AI technologies in practical applications.

The Senior Machine Learning Engineer will enhance mapping capabilities using ML, collaborating with cross-functional teams, analyzing data, developing models, and deploying solutions.

The Machine Learning Engineer will develop and deploy AI/ML models to enhance security, improve model performance, and respond to new threats in the Coinbase platform. Responsibilities include collaborating with stakeholders and applying advanced ML techniques.

The role involves applying advanced machine learning techniques to improve customer interactions, mentoring engineers, and designing scalable systems at Coinbase.

As a Senior Machine Learning Engineer, you will own a risk domain, architect ML systems, mentor engineers, and apply advanced ML methodologies to enhance security measures against fraud and scams.

Seeking a Senior Staff Machine Learning Engineer to lead AI/ML model design and implementation for fraud detection and risk management, collaborating across teams to enhance security systems.

Lead the design and deployment of AI/ML solutions for grid automation, manage teams, drive innovation, and ensure adherence to architectural standards.

The Machine Learning Engineer will design and optimize processing pipelines for video translation, ensuring efficiency and reliability of AI systems while collaborating cross-functionally.

The Machine Learning Architect will design and implement AI/ML solutions using cloud platforms, working closely with customers to meet their business goals.

The Senior Machine Learning Engineer will design and optimize ML discovery features, oversee projects, mentor engineers, and manage the ML lifecycle from data ingestion to model deployment.

As an Ecommerce Machine Learning Intern, be involved in developing and training machine learning models, collaborating effectively within teams, and applying insights for personalized recommendations.

Develop end-to-end software agents as collaborative AI teammates to empower engineering teams in solving complex challenges.

Develop scalable machine learning models, collaborate with DevOps and Data teams, create proofs of concept, and ensure high-quality software development.

As a Research Engineer, you will develop and enhance AI algorithms for self-driving vehicles, collaborating with scientists to advance technology and support deployment in production systems.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

Develop and launch machine learning algorithms for Lyft's core services; collaborate with teams to apply ML for business impact and evaluate systems against goals.

The Senior Machine Learning Engineer will develop and enhance machine learning models and advanced analytics, collaborating with teams to deliver impactful, scalable AI solutions.

The Machine Learning Engineer will develop and optimize ML models, build scalable pipelines, and enhance model performance while collaborating with teams to deliver impactful AI solutions.

As a Machine Learning Engineer at Lyft, you will develop and launch algorithms that power core services, perform data analysis, and build ML models in collaboration with cross-functional teams.

The AI/ML Engineer will design and maintain scalable ML infrastructure, implement ML technologies, and optimize ML systems, collaborating with cross-functional teams to enhance Okta’s AI/ML capabilities.

This role involves leading MLOps initiatives to automate Machine Learning workflows on GCP, collaborating with various stakeholders and ensuring efficient project delivery.

The ML Developer will develop and optimize machine learning models, integrate AI features into applications, and collaborate with teams for best practices in AI solutions.

Design, develop, and deploy scalable machine learning solutions, integrate ML with data warehouses, and optimize model performance in production environments.