Top Machine Learning Jobs in Toronto

As a Machine Learning Intern, you will assist in developing, training, and deploying machine learning models, collaborating with data scientists.

The Machine Learning Engineer / Data Scientist will build and deploy machine learning solutions, working through the ML lifecycle from problem framing to production.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The role involves developing infrastructure for benchmarking AI inference performance, analyzing system behavior, designing telemetry systems, and collaborating with teams to improve feature performance.

The ML Platform Engineer enhances the ML platform's performance and scalability, supports machine learning solutions, and leads software development efforts.

The Staff Software Engineer will enhance the ML platform's performance and scalability, collaborating with teams to support predictive modeling and real-time inference capabilities.

Lead the design and implementation of ML models and systems for auto-labeling in robotics. Collaborate across teams and mentor junior engineers.

Design and deploy production ML models for pricing decisions at Lime, collaborating with engineers, mentoring teams, and influencing strategy.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

Design and deploy ML solutions for video analytics. Build MLOps pipelines, collaborate on product features, and troubleshoot AI/ML issues.

The Senior Software Engineer II, Machine Learning will design and deploy ML algorithms, work with consumer data, and lead data teams.

Responsible for developing and deploying AI/ML models, integrating systems, optimizing LLM performance, and implementing MLOps practices within GCP.

As a Senior Machine Learning Engineer, you will design, develop, and deploy ML systems, mentor team members, and collaborate on advanced AI applications in tax research.

As a Machine Learning Intern at Pinterest, you will lead ML projects, analyze data, build models, and collaborate with teams to solve complex problems.

As an Associate AI/ML Developer, you'll build AI platforms, support AI pipelines, maintain AI/ML tools, and ensure model quality and monitoring while collaborating with teams on governance and security.

The Senior ML Platform Engineer will develop scalable machine learning solutions, manage ML infrastructure, and ensure observability in ML workflows while collaborating with cross-functional teams.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The Machine Learning Architect will design ML systems, mentor teammates, and work with AWS to deliver solutions, ensuring alignment with customer needs and technical requirements.

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

Design and implement system-level debugging, validation, and observability platforms. Build automated anomaly detection, visualization and analysis tools, and frameworks for failure classification and regression detection. Extend compilers, runtimes, and instrumentation for advanced profiling. Improve bring-up and low-level debug workflows, partner cross-functionally across hardware, firmware, compiler and runtime teams, lead high-impact initiatives, and support incident response and long-term corrective actions.

Lead design, implementation, and optimization of large-scale ML models and recommender systems for ad-tech and mobile gaming. Oversee end-to-end data science projects, deploy production DNNs, build A/B testing frameworks, mentor junior staff, and collaborate with Product, Marketing, and Engineering to drive user personalization and monetization.

As a Staff Machine Learning Engineer, you will design scalable AI infrastructure, implement AI systems, lead technical decisions, and collaborate with teams to enhance AI/ML solutions.

Design and lead end-to-end AI/ML and GenAI architectures (data pipelines, training, inference, MLOps). Advise clients, integrate LLMs, build RAG systems, benchmark platforms, mentor teams, ensure responsible AI, and align ML strategy with business goals.

The Senior Machine Learning Engineer will develop and implement machine learning solutions, ensuring scalability, security, and adherence to best practices while collaborating with cross-functional teams.