Top Machine Learning Jobs in Toronto

Design, build, and improve ML systems and infrastructure, mentor junior engineers, and write maintainable code in a customer-focused environment.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

As a Machine Learning Support Engineer, you will address customer product issues, provide proactive guidance, and propose solutions to help clients succeed with Labelbox products.

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

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

As a Machine Learning Intern at Ema, you will work on building and deploying machine learning models, analyzing datasets, and collaborating with senior engineers in a fast-paced startup environment.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Senior Research Scientist at Clarifai, you will develop and optimize machine learning models, particularly in Computer Vision and GenAI, and collaborate across team to deliver innovative AI capabilities.

As a Senior Machine Learning Engineer, you will design ML systems for insights from data, manage the ML lifecycle, and develop recommendation systems through collaboration with cross-functional teams.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

Design, build, and scale ML systems for demand forecasting and vehicle positioning. Collaborate with teams and mentor engineers to enhance ML expertise.

Lead the Safety ML team as a technical lead, driving ML systems development for safety, collaborating with cross-functional teams, and tackling complex safety challenges.

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.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.