Top AI Jobs in Toronto

The Applied AI Specialist will design and maintain data pipelines for ML, prepare datasets, collaborate with AI engineers, and ensure data reliability for AI applications.

As a Senior Software Engineer, you will design, implement, and maintain backend systems that integrate identity and authorization capabilities into AI workflows, ensuring security and reliability at scale.

The Account Executive will manage the full sales cycle for enterprise and scale-up accounts, building relationships with technical buyers and collaborating closely with senior leadership to drive revenue and shape sales strategies.

As a Senior AI Kernel Engineer, you will design and optimize high-performance kernels for AI inference on GPUs and custom accelerators, improving performance and collaborating with various teams to influence architecture and implementation.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

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 Forward Deployed Engineer, you'll manage AI deployments in manufacturing, integrating systems, troubleshooting, and liaising between technical teams and customers.

Lead backend architecture design, develop core modules, optimize systems, and enhance AI integration for scalable products. Drive cloud-native microservices architecture using Kubernetes and Docker, ensuring performance and reliability in high-concurrency environments.

As a Fullstack Software Engineer, you'll collaborate with multi-functional teams to enhance AI-driven solutions, participate in software development best practices, and take ownership of various platform functional areas.

As a Fullstack Software Engineer, you'll enhance Evisort's AI-driven contract management platform by collaborating with cross-functional teams and taking ownership of multiple functional areas from development to production.

The Principal Platform Engineer will design and implement AI platforms, including distributed systems and orchestration frameworks, mentor engineers, and define best practices for LLM integration.

The Senior Platform Engineer will build AI systems, develop APIs, support scalability, and integrate AI capabilities for financial services clients.

The Sr. Machine Learning Engineer will design and deploy scalable ML systems, collaborate across teams, and ensure production readiness of ML models using modern frameworks and cloud services.

Develop production-grade AI agents for enterprise customers. Design and build LLM-powered systems, integrating workflows, evaluation, and performance standards. Collaborate closely with customers and teams to ensure reliability and effectiveness in real-world applications.

The role involves designing, developing, and implementing AI/ML solutions for Investment Banking products. Responsibilities include leading technical direction, mentoring junior engineers, collaborating with stakeholders, optimizing AI systems, and ensuring data quality for deployment.

The Applied AI Scientist will work on developing and deploying AI systems, collaborating across teams to improve product features and drive customer impact through machine learning models.

As an Applied AI Developer, you will build AI-backed tools using Python, integrating LLM APIs, and automating workflows while ensuring reliability and quality evaluation of AI outputs.

The Co-op Engineer will analyze source code, implement new features on demo apps for Android or HarmonyOS, and deploy AI models on Huawei devices, collaborating across teams.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Develop and deploy AI agents, integrating them with external systems and optimizing performance in multi-agent environments. Collaborate with product managers to align agent capabilities with business needs, exploring technologies in Generative AI and LLM orchestration.

As a Staff Applied AI Engineer at Invoca, you'll architect and deploy AI systems, engineer advanced RAG systems, contribute to AI evaluations, optimize prompts, and ensure scalable and reliable AI model serving.

The Research Engineer will develop the DeOS framework, optimizing AI workloads, managing GPU resources, ensuring scalability, and contributing to open-source projects.

Design and implement advanced generative AI models, optimize deployment in production, collaborate with teams, and stay updated on AI advancements.

The Managing Partner will lead enterprise sales, managing multi-million dollar pipelines and fostering strategic partnerships with AI labs and Fortune 500 clients.

The Solution Architect focuses on integrating and enhancing AI features within enterprise applications, driving operational excellence and hyperautomation across the organization.