Huawei Canada has an immediate permanent opening for a 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:
Conduct in-depth analysis and gain insights into mainstream products and advanced technologies in the data domain. Lead core technological breakthroughs and innovation in areas including big data engines, databases, data-AI integration, data engineering for large models, and hardware-software co-design for heterogeneous platforms. Explore the evolving direction of AI and big data/database, driving the advancement of cutting-edge technologies.
Formulate a comprehensive "Data+AI" technology strategy and roadmap, acting as a technical visionary on projects to ensure commercial success. Lead the development of data-domain products, creating industry-leading Data+AI solutions to meet the data processing demands of the large model era.
Attract top global talent in the data domain to build a world-class research team. Lead the team to deliver high-quality, competitive products, ensuring the leading position in the market. Serve as the Chair of the Big Data Committee, presiding over major technical design reviews and the decision-making process.
Engage with the big data industry and academic communities through conferences and other forums. Leverage open-source platforms and projects to enhance the influence of the Kunpeng architecture and its ecosystem in the AI and big data landscape.
About the ideal candidate：
In-depth understanding of the architecture and performance optimization of at least one major big data engines, such as Spark, Flink, Presto, HBase, or Hive.
Familiarity with the principle of databases like PostgreSQL and MySQL, with a profound understanding of distributed database architectures such as Shared-Nothing and Shared-Everything.
Deep understanding of the Data & AI domain with proven experience in design and development. Extensive experience in data engineering tailored for large models, knowing the specific data requirements.
Proven track record of successfully designing, developing, and delivering solutions involving hardware-software co-design for CPU + GPU/NPU environments.
Demonstrated contributions to architectural design and implementation of big data engine/database solutions, with remarkable commercial impact. Publications in top-tier conferences or patents in the big data field are preferred.
Proven experience in managing global R&D teams and leading them effectively across different time zones.
Familiarity with the ARM chipset and ecosystem is an asset.