Top Machine Learning Jobs in Toronto

The Software Engineer will focus on ML Ops, developing deep learning models, creating redundancy systems, and generating performance diagnostics, ideally with a robotics background.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

The Senior Machine Learning Engineer will develop scalable machine learning solutions and integrate them to meet business needs. Responsible for documentation, code reviews, and establishing best practices, this role requires collaboration with various stakeholders and providing technical guidance.

The Machine Learning Intern will design and train models, develop AI agents, and work with teams to create impactful applications.

The role involves designing and developing machine learning infrastructure for annotation, evaluation, and training models, focusing on scalable systems and efficient data workflows.

Develop AI solutions and enhance observability data using AI-powered features. Collaborate cross-functionally, iterate rapidly, and take ownership of AI projects while ensuring scalability and impact.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

You will lead full-stack development and manage engineering teams responsible for building scalable web platforms and search systems using ML techniques.

The role involves developing predictive models and machine learning algorithms, analyzing data, and collaborating with teams to create data-driven strategies and solutions.

As a Machine Learning Intern, you will model deep learning algorithms, run performance analysis, and collaborate with Data Scientists on developing Accelerator IPs.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Lead the development and deployment of advanced machine learning models focusing on NLP, while ensuring model integrity and communication with stakeholders.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

The Senior Software Engineer II, Machine Learning will design and deploy ML algorithms, work with consumer data, and lead data teams.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

The Principal Platform Engineer will design and build scalable ML platforms, develop cloud-native infrastructure, and manage the model lifecycle in enterprise environments, focusing on MLOps capabilities and mentoring engineers.

RAVL is seeking Senior ML Platform Engineers to build and scale machine learning platforms, develop ML pipelines, and support MLOps workflows in cloud environments.

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

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

Develop and deploy AI agents, integrating them with external systems and optimizing performance in multi-agent environments. Collaborate with product managers to align agent capabilities with business needs, exploring technologies in Generative AI and LLM orchestration.

Lead a team focused on data and ML systems at eBay, driving architectural decisions, product execution, and best practices in ML applications.

As an Engineering Manager for Inference ML Runtime, you will lead a team to design, scale, and optimize AI inference systems on Cerebras hardware, ensuring high performance and overseeing execution of ML engineering initiatives.

The ML Developer Experience Engineer will create tooling and workflows for ML developers, enhance customer adoption, and ensure high-quality developer experiences through collaboration and documentation.