Top Machine Learning Jobs in Toronto

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 intern will contribute to ML model design, coding, testing, collaborating with teams, and analyzing data to support decision-making.

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

Lead and grow a product engineering team at Butter Payments, focusing on product delivery, technical excellence, and team development while collaborating cross-functionally to drive business outcomes.

Manage AI product development, driving discovery, execution, and data-driven decisions to improve customer outcomes. Collaborate with teams.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Machine Learning Engineer role involves designing, implementing, and deploying ML solutions, focusing on LLMs and collaboration with engineering teams.

Lead the Listing Quality pod to improve product listings using machine learning, guide junior Data Scientists, and develop strategies.

Develop machine learning-powered search ranking models and enhance personalization for search and discovery to support local retailers in a growing marketplace.

Manage engineering programs for generative machine learning models, ensuring cross-functional alignment, process improvement, and communication flow to enhance project execution.

Lead R&D to design and deploy ML models for conversational agents, enhance automation in customer support, and build scalable AI systems across business units.

Develop and optimize hardware and software ML inference systems. Collaborate with teams to improve architectural decisions and trade-offs for performance optimization.

Responsible for developing machine learning models, conducting quantitative analysis, and optimizing workflows to enhance user experience and engagement at The Athletic.

As a Senior/Staff Machine Learning Engineer, you will design scalable data pipelines, implement ML algorithms, and collaborate with engineers and Data Scientists to optimize the digital advertising platform.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

As an Applied Machine Learning Scientist, you will innovate and develop machine learning algorithms, write production code, and collaborate to implement and test these solutions based on historical data.

The Data Scientist will conduct data analysis and modeling to support investment decisions, design data pipelines, and collaborate with teams to provide actionable insights.

As a Machine Learning Intern, you will lead projects, analyze data, write efficient code, and apply various ML techniques to solve problems at Pinterest.

Lead product strategy and execution for AI solutions in the financial sector, managing cross-functional teams and product lifecycle from ideation to delivery.

As a Key Account Manager at Nomic Bio, you will lead the expansion of pharmaceutical accounts, engaging with executives and coordinating with technical teams to drive the adoption of proteomic solutions in drug discovery.

Lead Developer Relations at Freeplay, focusing on community engagement, strategic content creation, and brand growth within the AI engineering space.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

As a Senior Solution Engineer, you will solve complex customer problems, support the sales team, conduct demos, and deliver proof of concepts for Snowflake's data solutions.

The Machine Learning Engineer will build models to detect fraud in Block's ecosystems, collaborate with teams, and enhance ML processes.