Top Python Jobs in Toronto

The researcher will focus on advancing AI in computer vision and autonomous driving, implementing generative AI models, mentoring staff, and managing projects. They will also contribute to patent filings and stay updated with industry research.

In this role, the researcher will specialize in computer vision and machine learning, developing algorithms, evaluating solutions, and collaborating with teams.

As a Co-op Researcher, you will engage in research and development in computer vision and machine learning, optimizing algorithms and models for mobile computing constraints.

The role involves advancing reinforcement learning techniques for LLMs, including designing training pipelines and evaluating agentic behaviors, contributing to scientific publications.

The Co-op Researcher will research and develop cutting-edge technology in machine learning and computer vision, focusing on algorithm optimization for mobile devices.

The researcher will focus on computer vision and autonomous driving, contribute to R&D, mentor junior engineers, and manage projects while collaborating with cross-functional teams.

Design, develop, and test software for compilers, language runtimes, and optimization of deep learning frameworks while collaborating in a project-based environment.

Lead cutting-edge research combining AI and computational sciences. Collaborate on AI infrastructure, prototype solutions, mentor junior researchers, and publish impactful findings.

Lead the design and deployment of AI multi-agent systems on cloud platforms, integrate AI models, and collaborate with a global team.

Develop and maintain GPU drivers on Linux, optimizing features, collaborating with teams, troubleshooting issues, and ensuring high coding standards.

The Researcher will lead research and development in computer vision and multimodal models, mentor junior staff, and drive innovation through publications and patents.

Engage in AI research to optimize systems on edge devices, develop efficient algorithms, and analyze AI model performance.

The Senior Compiler Engineer will design and develop software for various products, optimize systems, lead teams, mentor juniors, and research industry trends.

Assist in research and development of computer vision and machine learning technologies through deep learning and image analysis. Optimize algorithms for mobile deployment and contribute to projects involving image and video analysis.

Design and develop advanced RL algorithms, build simulation platforms, optimize multi-agent learning on distributed clusters, and translate research into production systems.

The Co-op Researcher role involves investigating autonomous driving problems, designing algorithms, prototyping ideas, and collaborating with researchers in AI advancements.

The intern will research and prototype AI agents and intelligent systems, analyze industry trends, develop experimental AI applications, and contribute to internal reports on emerging AI technologies.

The job involves conducting applied AI research, developing algorithms for computer vision, and producing impactful academic publications. The role requires collaboration with product teams and focuses on real-world application of AI techniques.

Conduct applied research to develop AI data engine and storage architectures for large-scale workloads, optimize system software, and advance AI storage technologies.

The Machine Learning Engineer will develop and deploy ML models for energy forecasting, build components for digital twin platforms, and collaborate across teams on practical solutions.

The Principal Compiler Engineer will design and optimize software for heterogeneous architectures, mentor junior developers, and drive project planning and innovation.

Lead architecture design and technology selection for foundation model applications, driving innovation and efficiency for AI developers, and connecting business and academic resources.

Conduct advanced research and prototyping in speech/audio AI, design deep learning architectures, develop audio AI capabilities, and collaborate with teams on innovative intelligent products.

Develop and implement AI risk assessment and pricing frameworks by evaluating AI models, creating rating tables and pricing models, collaborating with underwriters, building Python-based analytical tools, and researching emerging AI risks and mitigation strategies.

Conduct research into AI model behavior and failure modes; design and build models, agents, and automated evaluation pipelines to assess AI risk; develop production-grade tooling for continuous monitoring and model testing; create novel risk metrics; collaborate with underwriting and actuarial teams to translate findings into pricing signals; prototype and deploy robust, well-tested systems while communicating results to technical and non-technical stakeholders.