Senior Machine Learning Research Engineer - Acceleration of AI models

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Senior Machine Learning Research Engineer - Acceleration of AI models, Markham

Location: Markham, Canada

Job Category:

Information Technology

Job Reference:

w46lenyw

Job Views:

Posted:

Expiry Date:

17.04.2025

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 is 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 reports and proposals for promoting the Ascend system accordingly.
• Lead or participate in research of algorithms in accelerating the training of market-driven AI models (CV/NLP/GNN/…), reaching/exceeding state-of-the-art accuracy, and develop a proof of concept of the algorithms. These algorithms include but are not limited to optimizers, loss functions, new model architecture, mixed precision, model compression, learning technologies (e.g., meta-learning), etc.
• Publish relevant high-quality AI research papers when necessary and approved, and attend conferences to increase public awareness of Huawei’s Ascend products; file high-value patents on critical algorithms/processes that have potential business gain.
• Team up with other departments/teams from Huawei’s global research centers for collaboration.
• Assist the team lead in 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 of 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 presentations.
• Working knowledge of AI accelerators or the full stack of AI acceleration systems is an asset.
• Strong math background in optimization (e.g., gradient descent) is an asset.