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Join to apply for the Research Engineer - AI Computing System role at Huawei Canada.Get AI-powered advice on this job and more exclusive features.Huawei Canada has an immediate permanent opening for an Engineer.About the team:The Advanced Computing and Storage Lab, part of the Vancouver Research Centre, explores adaptive computing system architectures to address future challenges posed by flexible and variable application loads. The lab focuses on ensuring the stability and quality of training clusters, constructing dynamic cluster configuration strategy solvers, and establishing precision control systems to create stable and efficient computing power clusters. It also concentrates on key industry AI application scenarios such as large model training/inference, leveraging technologies like low-precision training, multi-modal training, and reinforcement learning to analyze bottlenecks and develop optimization solutions to enhance training and inference performance and usability.About the job:Focus on key industry AI scenarios such as large model training/inference, utilizing technologies like low-precision training, parallel strategy tuning, and training resource tuning. Responsible for bottleneck analysis of AI software systems on the Ascend platform and designing optimization solutions to improve training, inference performance, and usability.Design and develop optimization solutions for AI training/inference systems. Optimize architecture in computing, IO, and scheduling to build large-model AI training frameworks, operator libraries, acceleration libraries, and other software frameworks to support next-generation architectural innovations.Stay updated with the latest research and technological trends in AI computing cluster architecture, training acceleration, and inference acceleration to maintain and improve system competitiveness. The salary range for this position is $100,000 to $170,000, depending on education, experience, and expertise.Job requirements:Master's or PhD in Computer Science, Computer Engineering, AI, Software, Automation, Electronics, Communications, Robotics, or related fields.Knowledge of large model structures like Deepseek and Llama, with experience in large model training and inference optimization in LLM, MoE, multimodality, etc.Familiarity with hardware architectures and programming of AI accelerators such as GPU/NPU, with experience in hardware-software co-optimization.Preferred experience includes:Strong programming skills in Python/C/C++, good system design and coding habits.Ability to work independently, problem-solve, communicate effectively, and collaborate; keen on learning and practical application.Experience in developing AI training frameworks, reasoning engines, or related hardware/algorithm development is a plus.Strong research skills in new AI technologies and architectures, with the ability to quickly learn and lead innovations.Seniority levelEntry levelEmployment typeFull-timeJob functionEngineering and Information TechnologyIndustriesTelecommunications #J-18808-Ljbffr