Top Machine Learning Jobs in Toronto

Lead and manage Order Management system projects, drive cloud migrations, and collaborate with diverse teams to improve business processes using Oracle technologies.

As a Machine Learning Engineer, you will develop machine learning models for creditworthiness, collaborate with engineering teams, and implement data pipelines for production models.

As a Software Engineer in the Bidding Intelligence group, you will design and implement scalable systems, support ML model building, and optimize bidding strategies for mobile app growth.

As a Senior Backend Engineer at Roofr, you'll enhance backend architecture, collaborate with cross-functional teams, and drive software development while ensuring clean code and production support.

Lead the design and deployment of scalable machine learning systems, optimizing performance and collaborating with teams to create production-ready solutions.

The role involves leading the Data Engineering team, defining technical vision, collaborating with cross-functional teams, and managing engineers. Responsibilities include guiding complex technical decisions and fostering a high-performing culture.

As an AI Student, you will implement AI projects, develop machine learning models, collaborate with teams, and report on progress to improve production efficiency.

Lead GitLab's Custom Models team, manage high-performing engineers, and develop AI solutions tailored to customer needs while promoting innovation and collaboration.

The Senior Machine Learning Engineer will build and maintain ML infrastructure, develop MLOps solutions, and collaborate on API-enabled services and deployments.

Lead deployment of the secure AI platform North within enterprise environments, ensuring integration, troubleshooting issues, and providing training.

Responsible for optimizing AI cloud platform deployment, ensuring high reliability and scalability of distributed training and inference infrastructure, and developing tools to identify system bottlenecks.

The Principal MLOPs Engineer will architect and optimize an ML inference platform, collaborate with teams to meet business goals, lead engineering efforts, and mentor team members.

Design and develop state-of-the-art language models and ML systems. Collaborate with product teams and lead impactful ML projects in a fast-paced environment.

Develop and optimize algorithms for robotic products, implement control algorithms, validate models, mentor junior members, and enhance robotics software development.

The role involves deploying machine learning models in banking, collaborating across teams, and leveraging advanced data techniques to drive product growth.

As an Intermediate Machine Learning Engineer, you will develop evaluation techniques, manage large language models, and collaborate on AI feature implementations, ensuring product quality and performance.

As a Senior Machine Learning Engineer at Wisedocs, you will build and scale ML models for document analysis, collaborate across teams, and ensure system reliability and scalability.

The Solutions Engineer leads technical sales engagements, educates clients on AI and data solutions, and develops customer relationships to meet strategic needs.

As a Senior Machine Learning Modeler, you'll develop machine learning solutions for detecting financial crimes, collaborating with stakeholders and improving team efficiency.

The role involves building ML solutions to evaluate customer cash flow risks, supporting various products, optimizing decision-making using AI/ML, and collaborating across teams.

The Senior Machine Learning Engineer develops ML solutions for customer cash flow risk assessment, collaborates across teams, and enhances automated decision-making processes.

As a Senior Machine Learning Engineer, you'll lead ML modeling initiatives, develop scalable AI solutions, collaborate with teams, and mentor others while enhancing risk management practices.

The role involves designing and deploying machine learning models for customer support, enhancing AI systems, and collaborating across teams. The focus is on innovation in automation and user interaction.

Join Braze's Engineering team to design and scale their AI platform, focusing on software engineering best practices and clean coding in Python.

The Principal Machine Learning Engineer will architect and deploy advanced ML models, collaborate with teams on product innovations, and lead end-to-end model processes.