Senior Technical VP - AI & Efficient Deep Learning

Huawei Canada has an immediate permanent opening for a Senior Technical VP.

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:

• Spearhead algorithm competitiveness planning and research and development efforts to guarantee the product's industry leadership and commercial triumph.
• Conduct in-depth analysis of technological development trends in AI computing, providing invaluable insights and defining project roadmaps for key AI technologies.
• Lead the charge in algorithm innovation and establish a robust core technology framework, driving the forefront of advancements in the field.
• Assemble a team of industry-leading algorithm experts with unparalleled innovation capabilities, ensuring our products' algorithmic competitiveness secures the top position in the industry.

About the ideal candidate：

• Possesses a degree in Computer Science, Mathematics/Statistics, Engineering, or related fields, establishing a strong academic foundation for the role.
• Accumulates 5~10 years of hands-on experience in deep learning or its applications to NLP/Multimodal/Speech/CV, showcasing extensive expertise.
• Demonstrates a robust theoretical foundation with an in-depth understanding of state-of-the-art large models (Llama, GPT series, CLIP, BERT, etc.) and AI algorithms.
• Experience in leading the design and development of large-scale research, projects, or products, reflecting a proven track record of impactful contributions.
• Possesses knowledge across the full stack of AI technologies, including optimizers, model compression, sparse training, low-rank decomposition, AI frameworks, and software & hardware co-optimization, along with accelerators (GPU, TPU, etc.).
• Expertise in model efficiency optimization, encompassing considerations like throughput and time to accuracy. Familiarity with distributed training frameworks such as DeepSpeed, Megatron, torch.distributed, Colossal-AI is highly valued.
• A solid publication record at top AI conferences is considered a valuable asset, showcasing a commitment to contributing to the advancement of the field.