Top Machine Learning Jobs in Toronto

As a Senior Staff Machine Learning Engineer at WEX, you will design, implement, train, and maintain machine learning algorithms and systems. You will collaborate with AI and engineering teams to integrate AI into applications, manage version control, and develop RESTful APIs. Strong communication and problem-solving skills are essential, as well as proficiency in Python and cloud technologies.

As an AI/Machine Learning Engineer, you will design and implement applications centered around Generative AI, deploying large language models in cloud environments and collaborating with cloud architects and developers. Proficiency in Python is essential, alongside knowledge of cloud AI services and machine learning frameworks. You will also address customer problems and present your work effectively.

The Applied ML Engineer will work with the business development team to provide technical guidance and AI solutions to customers using MindsDB. Responsibilities include customer engagement, technical discovery, creating reference architectures, and integrating modern AI/ML libraries into customer solutions.

As a Machine Learning Engineer, you will collaborate with teams to design and deploy machine learning models, develop scalable AI applications, and optimize models using Google Cloud Platform and Vertex AI.

As a Machine Learning Researcher, you will engage with complex problems and propose solutions by staying current with machine learning advancements, conducting rigorous experiments, evaluating model performance, and iterating on architectures to optimize results. You will collaborate effectively and communicate clearly with both technical and non-technical stakeholders.

As a Machine Learning Software Engineer, you'll build and improve ML-powered systems, propose technical architectures, design and manage the ML pipeline, and ensure effective communication in a remote environment. Your role will focus on delivering real business impact through scalable machine learning solutions.

As a Senior Software Engineer in Machine Learning Infrastructure, you will design and implement infrastructure for training and deploying deep learning models. You will develop metrics, optimize training pipelines in distributed environments, measure model performance, and collaborate with various engineering teams to enhance self-driving technology.

As a Software (ML Product) Engineer, you will enhance the user experience of ML tools by optimizing workflows and processes. You will collaborate with technical product managers, contribute to defining efficient ML practices, and improve DVC, an open-source tool for machine learning. A strong background in deep learning and system design is necessary to transform current workflows and engage with the ML community.

As a PhD Machine Learning Research Intern at Cresta, you will collaborate with leading researchers and engineers, contributing to AI advancements by developing algorithms for product deployment. You'll analyze the efficiency and scalability of algorithms, communicate findings to stakeholders, and publish research in top AI venues.

The Machine Learning Engineer will develop and optimize ML models for recommendation systems, build infrastructure for retrieval, and utilize large-scale data to create feedback loops. The role involves incorporating state-of-the-art LLMs into traditional systems and requires a strong background in machine learning and backend engineering.

Senior Machine Learning Engineer role at Kayzen, revolutionizing AdTech with machine learning. Responsible for accelerating experimentation and deployment, robust model monitoring, collaborating with data scientists, productionizing pipelines, driving innovation, and championing software engineering best practices.

Hightouch is looking to hire a Software Engineer specializing in Machine Learning to expand their data activation products with an intelligence layer. The role involves working on personalization, product recommendation, automated experimentation, predictive audiences, content generation, and budget optimization using data warehouses and databases.

As a Software Engineer focused on Data, AI/ML, and Analytics at Canonical, you will collaborate on developing end-to-end data analytics and machine learning solutions. Your responsibilities include designing and maintaining solutions for both public/private clouds, working with open-source tools, and engaging with a distributed team.

As an ML Engineer, you will design and optimize machine learning algorithms, build and maintain data pipelines, and deploy models. You will collaborate with teams to integrate solutions, conduct research on new technologies, monitor model performance, and document processes, enhancing cybersecurity resilience for organizations globally.

The Machine Learning Engineer will design, implement, test, and deploy algorithms for robot manipulation tasks. Responsibilities include developing ML algorithms, translating objectives into ML problems, and integrating solutions into robotics workflows. The role requires a collaborative approach to drive innovation and technical mentorship for junior engineers.