Huawei Canada has an immediate permanent opening for a Principal Scientist.
About the team:
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.
One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.
About the job:
Build an accurate and universal AI performance model based on mainstream AI acceleration technologies to support theoretical analysis.
Track the emerging hardware designs in the industry, conduct in-depth insight and survey analysis, and identify the direction of key cutting-edge technologies.
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.
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.
Lead our team for acceleration algorithm breakthrough in best tradeoff between model quality and compute efficiency.
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.
About the ideal candidate:
Master's or Doctoral degree in Computer Science or Electronic Engineering.
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.
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.
Familiarity with microarchitecture of AI chips is an asset.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Huawei Technologies provides innovative and customized network solutions for telecom carriers around the world. Huawei holds leading positions in the global market in switching, next generation network (NGN), integrated access network, DSLAM, and intelligent network. Specializing in the areas of fixed network, mobile network, optical network, data communications, and value-added services, we strive to enable the best communication with our deep understanding of customers' needs. Huawei is dedicated to delivering long term value and potential growth to our customers. Established in 1988 and headquartered in Shenzhen, China, Huawei has already won trust from over 300 telecom carriers around the world. Our products and solutions serve over 90 countries, as well as 22 of the world's top 50 operators. Huawei’s cloud computing products provide the reliability, agility, and price-performance needed for delivering cutting-edge applications and services quickly, safely, and securely to large scale of industry verticals. Our cloud deploys various popular technologies like Docker, Kubernetes, Mesos, Openstack, SDN/NFV, Hadoop, Spark, and many more. Huawei Public Cloud now mainly launched in China (and will spread to the other parts of the world) and Private cloud is deployed in several customer locations. Huawei has 400+ Worlwide Data Centers including several public/private cloud setups.