Top Machine Learning Jobs in Toronto

The Senior AI/ML Engineer will architect, build, and deploy AI systems, working with clients to understand their needs and applying MLOps practices to enhance AI services.

Develop scalable machine learning models, collaborate with teams, create proofs of concepts, and write maintainable code while engaging in the entire ML development cycle.

The Applied ML Engineer at Ideogram will turn generative models into production features, collaborate with teams to define metrics, and ensure ML systems' reliability.

Collaborate with engineers to build AI design systems, optimize data infrastructure, and manage large-scale distributed systems for model development.

The Senior Machine Learning Engineer will build and deploy NLP and LLM models, enhance system architecture, and collaborate with cross-functional teams for impactful outcomes.

The Sr. SoC Design Verification Engineer ensures functionality and performance of AI/ML accelerator chiplets by designing and executing test plans and collaborating with technical teams.

As a Staff Machine Learning Engineer, you'll design and deploy low-latency ML pipelines for ad delivery, collaborate on data integration, mentor engineers, and oversee business impact metrics.

Develop, deploy, and maintain scalable machine learning systems for real-time ad personalized targeting, collaborating with data science and engineering teams.

As an ML Solutions Architect, you'll lead technical discussions, design ML architectures for clients, and ensure scalable solutions. You'll also provide client-facing leadership and collaborate with delivery teams for successful project execution.

Lead the development of Dynamic Memory Management systems for LLM applications, integrating memory architectures, retrieval strategies, and model training for improved AI performance.

As a Senior ML Engineer, you'll design and deploy ML solutions, mentor junior engineers, and enhance ML practices and infrastructure.

The ML Tech Lead will provide technical leadership, mentor engineers, guide technical decisions, and contribute to complex ML projects and architecture.

The ML Solutions Architect will lead technical discussions, design ML architectures, and ensure client satisfaction through effective communication and deep technical expertise in ML solutions.

The Machine Learning Engineer will develop and deploy ML models, leveraging analytical skills to automate processes and reveal data value.

The role involves designing hardware and software for ML inference IP and compilers, focusing on FPGA development and optimizing performance.

Lead the design and deployment of AI/ML solutions for grid automation, manage teams, drive innovation, and ensure adherence to architectural standards.

The Senior Machine Learning Engineer will design and optimize ML discovery features, oversee projects, mentor engineers, and manage the ML lifecycle from data ingestion to model deployment.

The Machine Learning Intern will design and train models, develop AI agents, and work with teams to create impactful applications.

The Machine Learning Architect will design and implement AI/ML solutions using cloud platforms, working closely with customers to meet their business goals.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Lead the development and deployment of advanced machine learning models focusing on NLP, while ensuring model integrity and communication with stakeholders.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.