Top Machine Learning Jobs in Toronto

The Staff Machine Learning Engineer will build and integrate machine learning solutions to evaluate customer cash flow risk and support multiple products in Cash App. The role involves experimenting with modeling techniques and collaborating with finance, product, and engineering teams to enhance automated decisioning processes and optimize growth opportunities.

As a Senior Machine Learning Engineer, you will develop and enhance machine learning platforms and infrastructure, collaborate with stakeholders, and automate pipelines for model deployment and monitoring, ensuring high quality and scalability of ML solutions.

As a Senior Machine Learning Engineer at Cash App, you will develop machine learning solutions for risk management and fraud mitigation, working collaboratively with cross-functional teams. You will utilize your expertise in machine learning algorithms and data analysis to enhance product offerings for a diverse customer base.

As a Staff Machine Learning Engineer for Cash App's Risk team, you will develop ML solutions to mitigate risk and fraud, collaborating with cross-functional teams. You will utilize a deep understanding of machine learning algorithms and data analysis techniques to enhance products and protect the customer experience.

As a Platform Software Engineer at Cerebras, you'll optimize their AI cloud platform for model training and inference, focusing on latency, load balancing, and system reliability. Responsibilities include defining production requirements, implementing scaling strategies, managing API servers, and resolving system bottlenecks.

As a Senior Backend Developer, you will advance the Machine Learning Platform by developing scalable and fault-tolerant services, designing and maintaining machine learning services, collaborating with stakeholders to define complex system requirements, and integrating AI research innovations.

The Engineering Manager for Rider Quality at Lyft will build and lead a new team of Test Automation and Machine Learning engineers, driving quality standards for the Lyft app. Responsibilities include setting technical vision, coaching team members, and collaborating with cross-functional partners to ensure project completion.

As a Data Engineer at StackAdapt, you will design modular, scalable real-time data pipelines, implement custom machine learning algorithms, and work on microservice architectures for training and monitoring ML models. Collaboration with data scientists and engineers is key to solving complex data challenges in a rapidly evolving digital advertising space.

As a Senior Machine Learning Modeler, you will develop and implement statistical models using machine learning techniques to forecast business outcomes, collaborate across teams, and explore novel methodologies while effectively communicating results to senior leadership.

You will design, build, and maintain Machine Learning systems for identifying fraudulent activities. Collaborating closely with ML Modelers, you'll integrate new data sources and solve technical challenges across a global team. Your role involves owning solutions from design through operation while improving fraud detection capabilities.

The GCOA Enterprise Architect at Lilly is responsible for developing innovative technology solutions that enhance business productivity and efficiency. This role involves strategizing technology roadmaps, determining system architecture, aligning IT with business goals, and documenting processes through architectural models. The architect will work closely with stakeholders to ensure optimal technology usage and integrate emerging technologies into business processes.

As a Sr. Machine Learning Engineer, you'll innovate with cutting-edge machine learning technologies, build scalable ecosystems, and create backend microservices. You'll also maintain data pipelines, collaborate with teams, and emphasize coding quality in a flexible, agile environment.

As a Staff Software Engineer in Machine Learning Infrastructure at Thumbtack, you'll lead the technical vision for the company's ML platform. Responsibilities include defining architecture for scalable ML systems, establishing best practices, and mentoring engineering teams. You will work with cross-functional teams to align ML capabilities with business objectives.

As a Machine Learning Engineer, you'll work on developing and deploying machine learning models for a content recommender system, collaborating with data engineers to enhance data collection and features. You'll analyze customer behavior and conduct A/B tests to improve system performance.

In this role, you will design and develop AI systems, build scalable ML solutions for SaaS applications, collaborate with data scientists, and manage databases for model training. You'll participate in the lifecycle of ML model development, ensuring efficient deployment and integration into production environments while staying updated on ML technologies.

As a Senior Machine Learning Engineer, you will build the Cashbot, develop high-quality customer support experiences, and create modeling pipelines while collaborating with Product, Design, and Engineering teams. You will focus on improving chatbot functionality and mentoring other team members.

As the Director of Engineering for Machine Learning, you'll lead multiple teams to advance deep learning applications in robotics, manage large teams, and develop collaborative relationships to drive technical vision in autonomous driving.