Top Machine Learning Jobs in Toronto

Develop, design, and maintain advanced NLP applications and LLM projects for Poe, contributing to a scalable machine learning system and user features.

The role involves building and maintaining large-scale distributed systems for ML development, collaborating with teams and resolving production issues.

As a Machine Learning Engineer, you will develop and train models for data knowledge extraction, fine-tune LLMs, and collaborate across data infrastructure.

As a Founding Engineer, you will guide the technical direction and build GPU infrastructure for real-time AI, optimizing inference engines and engaging with customers.

As a Machine Learning Ops Developer at Autodesk, you'll collaborate on AI tools for the AEC industry, developing data pipelines and models, while ensuring accuracy and performance of AI applications.

As a Senior Machine Learning Engineer, you will develop machine learning models and infrastructure to support AI products, ensuring security and performance.

Develop and refine evaluation methodologies for AI models, design evaluation systems, collaborate with product teams, and contribute to long-term research in answer quality.

The Machine Learning Developer will enhance and optimize ML models, build distributed ML platforms, and collaborate with Data Science teams at Counterpart Health to improve patient outcomes.

Lead and manage the Ads Engagement Modeling Team to develop machine learning models that enhance user engagement on Reddit through predictive modeling and cross-functional collaboration.

Design and deploy machine learning algorithms, work with large datasets, and provide leadership for data teams in various applications.

As a Machine Learning Engineer, you will develop and deploy large-scale ML models and algorithms, using data to automate processes such as image classification and speech recognition while collaborating with other technical professionals.

As a Machine Learning Engineer, you'll design and optimize algorithms for AI solutions, collaborate with teams, and enhance existing systems.

Responsible for leading machine learning engineering teams, optimizing ML systems, and ensuring delivery of scalable, reliable solutions while managing team performance and collaborating with cross-functional partners.

Design and implement REST APIs for AI/ML services. Optimize databases on AWS for low latency, and improve system reliability and security.

Lead the design, development, and optimization of ML systems using generative models. Collaborate with research to improve models and productionize solutions.

The Machine Learning Engineer will develop AI algorithms for the AI Companion product, collaborate with teams, and enhance existing systems.

Lead the AI/ML platform development, design architecture, mentor teams, partner with stakeholders, and ensure quality and security in solutions.