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Senior Machine Learning Research Engineer Acceleration of AI models

Senior Machine Learning Research Engineer Acceleration of AI models

Huawei Technologies Canada Co., Ltd.Markham, ON, CA
30+ days ago
Job type
  • Permanent
Job description

Huawei Canada has an immediate permanent opening for a Senior Research Engineer.

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 :

  • Track the trend of AI theory and technology development in the world and generate research report and proposals for promoting Ascend system accordingly.
  • Lead or participate in research of algorithms in accelerating the training of the market-driven AI models (CV / NLP / GNN / …), reaching / exceeding the state of the art accuracy, and develop a proof of concept of the algorithms. Those algorithms include but are not limited to the following : optimizers, loss functions, new model architecture, mix precision, model compression, learning technologies (e.g., meta-learning), etc.
  • Publish relevant high-quality AI research papers when necessary and approved, and attend conferences for increasing public awareness of Huawei’s Ascend products; file high-value patents on critical algorithms / processes that are of potential business gain.
  • Team up with other departments / teams from Huawei’s global research centers for collaboration.
  • Assist the team lead on the planning of projects and definition of technology / products development road map.

About the ideal candidate:

  • Master or PhD in Computer Science, Math / Statistics, focusing on AI & Deep Learning with solid publication records.
  • 2+ years working experience in optimizing performance of training deep learning models and / or their applications to CV / NLP / GNN domains.
  • Solid skills in programming in Tensorflow / Keras / PyTorch / MXNet.
  • Hands-on skills in C++ / Python programming.
  • Excellent documentation skills in writing internal reports and / or publishing research papers.
  • Excellent communication skills in internal and external presentation.
  • Working knowledge of AI accelerators or the full stack of AI acceleration system is an asset.
  • Strong math background in optimization (e.g., gradient descending) is an asset.
  • LI-SZ2