Principal Scientist - Software/Hardware Co-design

Job Description

<p><strong><span>Huawei Canada has an immediate permanent opening for a Principal Scientist.</span></strong></p><p><strong><span>About the team:</span></strong></p><p>The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications.</p><p>One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.</p><p><strong><span>About the job:</span></strong></p><ul><li><p><span>Build an accurate and universal AI performance model based on mainstream AI acceleration technologies to support theoretical analysis.</span></p></li><li><p><span>Track the emerging hardware designs in the industry, conduct in-depth insight and survey analysis, and identify the direction of key cutting-edge technologies.</span></p></li><li><p><span>Cooperate with our AI research team to identify key performance bottlenecks in future AI workloads, and define key algo-hw codesign features of our next-generation chips, for the objectives of low cost, high throughput, great scalability, and stability.</span></p></li><li><p><span>Performance modelling of representative AI workloads with state of the art training & inference algorithms on different hardware specs for quantitative analysis of compute, memory, IO and interconnect.</span></p></li><li><p><span>Lead our team for acceleration algorithm breakthrough in best tradeoff between model quality and compute efficiency.</span></p></li><li><p><span>Track the emerging algorithm-hardware codesign technologies in the industry, conduct in-depth insight and survey analysis, and deeply understand main directions and trends of cutting-edge algorithm-hardware codesign technologies.</span></p></li></ul><br><p><strong><span>About the ideal candidate:</span></strong></p><ul><li><p><span>Master's or Doctoral degree in Computer Science or Electronic Engineering.</span></p></li><li><p><span>At least 5+ years of experience in low-level computing algorithm development, AI accelerator/ large scale parallel computing / high performance computing system design is an asset.</span></p></li><li><p><span>Deep understanding of the basic principles and workload characteristics of large language models / multimodal models, the popular AI software stack (operators, compilers, acceleration libraries, frameworks) and mainstream large model training and inference algorithms, such as hybrid parallelism, low precision data formats, sparsity, P/D splitting, etc.</span></p></li><li><p><span>Familiarity with microarchitecture of AI chips is an asset.</span><br><br></p></li></ul>
#J-18808-Ljbffr