Top Machine Learning Jobs in Toronto

Lead the engineering vision and execution for the Customer & Business Insights Platform, focusing on data architecture, pipelines, and product delivery while mentoring global teams and ensuring data governance.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

Lead the pricing intelligence, supplier performance, and financial reconciliation for travel segments, utilizing AI and model-driven systems.

The Forward Deployed Research Scientist engages directly with AI labs to develop data strategies, fine-tune models, run experiments, and collaborate on publishing research, all in a fast-paced client-focused setting.

Develop AI-powered features, design APIs, integrate AI/ML models, and enhance developer experience for ClickHouse's platform.

As a Machine Learning Ops Engineer, you'll develop robust code, build and maintain MLOps infrastructure, QA systems, and mentor junior engineers to enhance AI model performance for mining clients.

As a Forward Deployed ML Engineer, you will apply machine learning to mining operations, develop neural network architectures, and communicate findings to non-technical stakeholders while working independently.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

The Territory Account Executive manages sales strategies and customer relations in the Mid-Market sector, driving new business and territory growth.

The role involves leading the development of ML/AI systems, designing data pipelines, deploying ML models, and collaborating across teams to establish best practices.

As a Machine Learning Engineer at Stripe, you will design and deploy AI/ML models, drive system enhancements, and collaborate with cross-functional teams to achieve business goals.

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.

As a Machine Learning Engineer, you will optimize deep learning models, develop LLM training pipelines, implement model compression, and collaborate with research to enhance AI capabilities.

Design and deploy scalable machine learning solutions using AWS and Snowflake. Collaborate with cross-functional teams to optimize ML pipelines and mentor junior engineers, ensuring data security and best practices in MLOps.

The Intermediate Machine Learning Engineer will design ML pipelines, collaborate with teams, support model deployment, and ensure data compliance. The role requires proficiency in Python and experience with AWS and Snowflake.

This internship involves developing machine learning approaches for biological data, designing experiments, collaborating on research, and presenting findings.

Develop and deploy AI solutions for enterprise clients, focusing on large language models and agentic systems integration while ensuring quality, scalability, and security.

Manage and lead a team of engineers, oversee software development for ML platforms, and ensure high-quality project execution while collaborating across teams.

The role involves building scalable ML models, mentoring engineers, translating business requirements into specs, and ensuring solutions meet performance constraints.

Lead development of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks to enhance molecular engineering and experimentations.

The role involves designing de novo frameworks for molecular engineering, collaborating across teams to optimize data-driven biological experiments and integrating ML models with experimental systems.

The ML Research Scientist will design Bayesian optimization frameworks, collaborate with lab scientists, and integrate ML models with experimental data.