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Principal Architect - Large Model and Training System Performance Optimization
Principal Architect - Large Model and Training System Performance OptimizationHuawei • Vancouver, Metro Vancouver Regional District, CA
Principal Architect - Large Model and Training System Performance Optimization

Principal Architect - Large Model and Training System Performance Optimization

Huawei • Vancouver, Metro Vancouver Regional District, CA
Il y a plus de 30 jours
Type de contrat
  • Permanent
Description de poste

Huawei Canada has an immediate permanent opening for a Principal Architect

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 :

  • Lead the architecture design of Ascend training products, driving the continuous evolution of architectural competitiveness.
  • Analyze mainstream scenario requirements and industry technology trends for Ascend, introducing innovative technologies to ensure sustained leadership in architectural competitiveness.
  • Identify requirements for MindX, AI frameworks, acceleration libraries, and chip hardware, building a robust software-hardware architecture for Ascend training to achieve ongoing commercial success.
  • Collaborate with other departments / teams from Huawei’s global research centers to align on strategic goals.
  • Spearhead project planning and define the technology / product development roadmap to guide long-term innovation.

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

About the ideal candidate :

  • Master’s or PhD in Computer Science, Math / Statistics, with a focus on AI & Deep Learning.
  • 5+ years of experience in architecting large-scale AI training systems or similar complex software-hardware integrated solutions.
  • Excellent documentation skills for writing internal reports and / or publishing research papers. Effective communication skills for presentations to internal and external audiences. A proactive attitude with a strong ability to tackle challenges and adapt to evolving requirements and dynamic work environment.
  • Working knowledge of AI accelerators or full-stack AI acceleration systems and Deep Reinforcement Learning.
  • Hands-on experience with veRL or Ray for large-scale model training.
  • Familiarity with processor architectures and relevant work experience, with hands-on expertise in designing and developing complex system software architectures, and experience in performance optimization on GPU / NPU or similar hardware platforms.
  • Solid understanding of deep learning fundamentals, proficiency with the PyTorch framework, and practical experience in performance optimization using upper-layer distributed frameworks such as Megatron or DeepSpeed.
  • Strong programming skills with proficiency in C / C++ and Python.
  • Experience using performance analysis tools such as Nsight Systems, Nsight Compute, and DLProf.
  • #J-18808-Ljbffr

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