Top Machine Learning Jobs in Toronto

This role involves leading MLOps initiatives to automate Machine Learning workflows on GCP, collaborating with various stakeholders and ensuring efficient project delivery.

Develop and deploy models for the Piai claims-intelligence platform using machine learning, NLP techniques, and collaboration with various teams.

This role involves owning and evolving the ML platform, driving architecture standards, leading initiatives, and mentoring engineers to enhance ML capabilities at Faire.

As a Senior Product Manager, you will own product outcomes, develop roadmaps, translate market insights into action, and navigate technical complexities in a startup environment.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

As a Senior Machine Learning Engineer, you'll own ML systems, design scalable pipelines, ship LLM features, and guide ML adoption. You will mentor engineers and ensure system reliability and observability while engaging in high-impact work.

As a Staff Machine Learning Engineer, you will architect ML systems, mentor engineers, set technical direction, and drive ML workflows at scale.

Lead a team of data scientists and AI engineers to deliver AI-driven solutions and drive business impact through innovation and collaboration.

As a Product Manager for Risk, you'll design fraud prevention tools, manage cross-functional teams, and improve fraud detection methods.

Lead the development of AI-driven automation for security operations, focusing on integration, scalability, and accuracy of systems to enhance security efficacy.

Contribute to core ML infrastructure by designing and building training infrastructure, optimizing model integrations, and collaborating with data teams to implement pipelines.

As a Senior Solution Engineer, you'll guide customers in understanding AI solutions, conduct technical assessments, deliver demos, and provide strategic advice on digital transformation.

The Senior ML Performance Engineer will architect a Performance Testing Platform, optimize ML performance on GPUs, and validate model efficiency.

The role involves developing AI-powered solutions for e-commerce, optimizing data pipelines, and deploying ML systems at scale while using technologies like React, TypeScript, and AWS.

The Senior B2B Marketer will develop and execute marketing strategies, collaborate with sales, create materials, and conduct market research to drive growth in the gaming and 3D industries.

Seeking a Senior AI/ML Engineer to design and develop AI-native systems using Generative AI and multi-agent frameworks for real-time networking solutions. Responsibilities include modeling agent behaviors, developing LLM-driven agents, building ML models, and collaborating on AI projects.

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

As a Senior Machine Learning Engineer specializing in Reinforcement Learning, you will develop and deploy RL solutions, optimize ML models, and lead client discussions while ensuring high-quality engineering practices are followed.

The Senior Machine Learning Ops Engineer will design and build machine learning operations infrastructure, manage ML pipelines, experiment tracking, model deployment, and collaborate with engineering teams to enhance data and ML processes.

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

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The role involves developing and implementing AI/ML solutions for investment applications, analyzing data, and collaborating with investment teams to enhance decision-making through AI-driven insights.

The Data & ML Platform Engineer will design and implement data and ML components, optimize data ingestion, support architecture transformation, and drive automation and improvement of workflows.

As an AI/ML Solutions Architect, you will design scalable AI/ML architectures, engage with customers, and create thought leadership content to drive AI/ML adoption.