Top Machine Learning Jobs in Toronto

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

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.

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

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.

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

As an AI/ML Product Manager at Versapay, you'll manage products that leverage machine learning solutions, drive change, and enhance customer experience across platforms from ideation to implementation.

As an ML Engineer, you will develop and deploy machine learning solutions, design robust pipelines, and collaborate with cross-functional teams to improve key performance indicators in the travel industry.

Build and refine machine learning models for AI detection, develop scalable ML systems, and collaborate with design and product teams to create impactful applications.

The Staff Machine Learning Engineer will develop and deploy advanced AI/ML solutions, focusing on product features like predictive analytics and risk assessments, using LLMs and classical ML techniques.

As a Senior Software Engineer II in Machine Learning, you'll design and implement AI systems, focusing on production-grade ML techniques, collaborating with cross-functional teams, and ensuring systems are reliable and maintainable.

The Senior Machine Learning Engineer will build and enhance AI/ML solutions for risk management, using advanced techniques like LLMs and algorithms for predictive analytics and automated assessments.

Design, build, and optimize ML systems for recommendations at scale. Collaborate with teams on data pipelines, model development, and experimentation.

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

Lead a team of ML engineers and consultants to deliver AI/ML solutions on AWS while driving strategy, technical innovation, and practice development.

The Machine Learning Engineer develops and deploys models to optimize demand forecasting and vehicle positioning, collaborating with cross-functional teams to enhance rider experience.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

The Staff Data Scientist will enhance Pinterest's Curation by developing models and frameworks to understand and improve recommendation systems, influencing product strategy and mentoring junior scientists.

The Staff Machine Learning Engineer will develop advanced Document AI models, solve complex modeling challenges, lead LLM fine-tuning, and provide leadership in a collaborative environment.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

As a Machine Learning Scientist at LMArena, you'll lead open-source research, design experiments, and develop methodologies to evaluate AI models, collaborating across teams and engaging with the research community.

The Senior Software Engineer will lead the design of scalable, high-performance real-time data and API infrastructure, ensuring reliability and guiding engineers in best practices.

The Machine Learning Scientist will design experiments, analyze data, develop evaluation methods, and collaborate on AI model research and production.

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.

Design, build, and improve ML systems and infrastructure, mentor junior engineers, and write maintainable code in a customer-focused environment.