Senior Technical VP - AI & Efficient Deep Learning

Huawei Technologies Canada Co., Ltd.; Markham; On-site; CAD 150,000 - 250,000; Full time

Job summary

Huawei Technologies Canada is seeking a Senior Technical VP to enhance AI computing capabilities. This role involves leading the technology roadmap, optimizing system performance, and innovating AI chip architecture. The ideal candidate will possess extensive experience in AI with a solid publication record.

Qualifications

• Deep understanding of AI theory and proficiency in SOTA large-scale models.
• More than 5 years hands-on experience in AI fields like CV, LLM.
• Publication record in top-tier AI conferences preferred.

Responsibilities

• Lead the core competitiveness planning and technology roadmap in AI computing.
• Conduct in-depth analysis of technological trends in AI.
• Drive industry-leading AI system solutions through hardware/software/algorithms co-design.

Skills

AI Theory

Mathematical Knowledge

Hardware/Software Co-design

Computing Efficiency Optimization

Distributed Training

Education

Degree in Computer Science, Mathematics/Statistics, Engineering, or related fields

Job description

Huawei Canada has an immediate permanentopening for a SeniorTechnical 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:

• Conduct in-depth analysis of technological trends in the AI field, lead the core competitiveness planning and technology roadmap in AI computing, and ensure industry-leading product performance and commercial success in future AI inference & training applications.

• Deeply understand the chip and system architecture, and implement system-level innovation through co-design of hardware/software/algorithms. Build the core technical framework of AI computing systems, driving industry-leading AI system solutions.

About the ideal candidate：

• Degree in Computer Science, Mathematics/Statistics, Engineering, or related fields, with solid mathematical knowledge. Deep understanding of AI theory and proficiency in SOTA large-scale models (such as Llama and DeepSeek) and fundamental AI algorithm principles.

• Knowledge about AI chip architecture and interconnection technologies. Proficiency in hardware/software co-design and optimalization. In-depth understanding of key technologies in AI systems, including high-performance operator libraries, collective communication libraries, distributed acceleration, parallelism strategies, and efficient dispatching systems.

• Experience in computing efficiency optimization of large models, including optimization of inference latency and throughput, and MFU enhancement. Familiarity with distributed training and inference frameworks such as Megatron, vLLM, and SGLang.

• More than 5 years of hands-on experience in AI fields such as CV, LLM, MultiModal, Reasoning, and Agent. Experience in leading large-scale inference/training system research projects or product design & development, demonstrating outstanding commercial results and significant technical influence.

• Publication record in top-tier computer architecture/computer system/AI conferences is preferred.