Senior Engineer - Large Model and Training System Performance Optimization

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.

• 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.

The base salary for this position ranges from $121,000 to $230,000 depending on education, experience and demonstrated expertise.