Top Machine Learning Jobs in Toronto

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

The role involves designing and implementing ML pipelines, optimizing models for production, collaborating with scientists and engineers, and ensuring responsible AI practices.

Conduct innovative AI research in various advanced algorithms, collaborate with teams, and implement machine learning solutions to drive business transformation.

The Senior Cloud Engineer - Data & AI leads the development of data and AI products, ensuring alignment with business requirements and technical standards, while promoting innovation and process improvement.

Lead the architecture for AI/ML integration in Wealth and Asset Management applications, modernizing legacy systems, and mentoring teams while ensuring robust governance and performance standards.

The Principal Machine Learning Infrastructure Researcher will drive innovation in hardware systems for AI, collaborate on designs, publish research, and lead a team of engineers.

As a Senior/Principal Machine Learning Engineer, you will design and build core ML systems for Workday's AI agents, owning the entire lifecycle from problem framing to deployment and improvement, while collaborating cross-functionally to create scalable solutions.

As a Machine Learning Engineer, you will develop user experiences using LLMs and predictive analysis, deliver ML solutions, and ensure continuous improvement in AI products at scale.

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

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

The Software Engineer II will develop and deploy machine learning systems, manage model performance, and collaborate on AI solutions while ensuring reliability and scalability.

As a Machine Learning Engineer, you will optimize deep learning models, develop LLM training pipelines, implement model compression, and collaborate with research to enhance AI capabilities.

Lead technical design and development of Generative AI and Machine Learning systems at CIBC, overseeing project lifecycles and supporting engineering teams.

Design and develop MaintainX's search and data retrieval platform, optimizing distributed systems for performance and scalability, while collaborating on search modeling and integrating backend services.

The Machine Learning Engineer will design, develop, and deploy ML pipelines, optimize models, collaborate on data workflows, and implement MLOps best practices in a fintech environment.

Lead development of predictive models, define AI strategy, guide MLOps efforts, and ensure governance in AI deployments. Collaborate across teams to optimize outcomes and model performance while mentoring peers.

The role involves leading the development of predictive modeling, AI strategy, and MLOps to optimize business outcomes in retail, while collaborating with cross-functional teams and ensuring scalability and governance in AI deployment.

Lead the definition and rollout of AI-powered product features, collaborating with teams to enhance fraud prevention solutions.

The AI/ML Engineer will design, build, and deploy AI systems, manage data pipelines, collaborate with cross-functional teams, and support project management tasks in a remote setting.

As a Machine Learning Engineer at Stripe, you will design and deploy AI/ML models, drive system enhancements, and collaborate with cross-functional teams to achieve business goals.

The role involves leading the development of ML/AI systems, designing data pipelines, deploying ML models, and collaborating across teams to establish best practices.

Design and implement a scalable MLIR-based compiler framework for cloud-based AI inference, collaborating with multiple teams to optimize model deployment.

Lead data science projects using Visa's datasets, developing models and ML pipelines to provide actionable insights, mentoring junior team members, and engaging with clients to solve data-driven challenges.

You will design and build scalable ML infrastructure services, improve productivity for ML engineers, and enhance MLOps across the company.

Lead a multidisciplinary team to design and deliver agentic AI systems for drug discovery and clinical research, set technical roadmaps, ensure regulatory compliance and AI safety, mentor staff, and represent Sanofi in research collaborations.