Top Machine Learning Jobs in Toronto

The Staff ML Research Scientist will pioneer deep learning architectures for drug discovery, driving technical strategy and mentoring junior researchers.

As a Staff ML Research Engineer, you will architect and optimize ML models for drug discovery while ensuring technical excellence throughout the product lifecycle.

Lead the development of the Wildfire Fuel Detection Model using ML techniques and geospatial data, collaborating with teams to ensure accuracy and robustness. Mentor engineers and drive architectural decisions.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

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

The Account Executive will drive sales, develop strategies for business growth, manage accounts, and lead collaborations with clients and teams in the insurance sector.

As an Account Executive, you will drive new business opportunities and manage existing accounts in the telecom sector, contributing to revenue growth and sales strategy execution.

Lead Machine Learning Engineer responsible for setting technical vision, guiding teams, architecting solutions, and overseeing project delivery on Google Cloud. Requires strong ML fundamentals and excellent communication skills.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

As an ML Engineer, you will develop and deploy machine learning solutions, design robust pipelines, and collaborate with cross-functional teams to improve key performance indicators in the travel industry.

Design and implement ML and graph-ML solutions to analyze, extract, and generate knowledge from heterogeneous biomedical data. Enrich and reason over a biological knowledge graph using classification, relationship discovery, RAG/LLM techniques, and production-ready models. Collaborate cross-functionally to architect, train, deploy, and monitor scalable ML systems and provide technical leadership on Knowledge Enrichment projects.

As a Senior Applied Machine Learning Engineer, you will leverage machine learning techniques to enhance search relevance and personalize user recommendations, working with large-scale data to solve complex problems.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

Define and enforce ML quality strategy and acceptance criteria across data, model, and system levels. Design evaluation suites, metrics, and test datasets; automate ML QA using Python and CI/CD; build test harnesses and quality gates for training and deployment; evaluate CAD RL outputs; mentor teams, participate in code reviews, and document findings.

The Senior Machine Learning Engineer will develop and optimize AI image generation models, monitor production issues, and collaborate on ML solutions for generative features.

Design and manage evaluation datasets, develop evaluation pipelines, score assistant quality using LLMs, and build observability for AI agents.

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

As a Senior Machine Learning Engineer, you will own the ML stack, develop generation systems, improve quality, collaborate cross-functionally, and build data pipelines.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

We seek a Machine Learning Engineer to develop, deploy, and optimize advanced ML systems, focusing on AI Agent evaluation and optimization across complex environments.

As a Machine Learning Engineer, you will develop and optimize AI models and systems, focusing on Information Retrieval and Natural Language Processing while working with exclusive datasets to deliver valuable solutions for customers.

As a Machine Learning Engineer, you'll develop scalable ML solutions using Google Cloud Platform and Vertex AI, collaborate with teams, and operationalize models from ingestion to monitoring.

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

The role involves building deep learning models for ad candidate retrieval and ranking, improving recommendation systems, and taking ownership of ML systems.