5-7 years of experience in the data and AI domain with a focus on big data engines and databases.
Proficiency in designing and developing large model data engineering solutions.
Experience with hardware-software co-design, specifically in CPU + GPU/NPU environments.
Deep understanding of distributed databases structures like Shared-Nothing and Shared-Everything.
A track record of impactful contributions in architectural design for big data solutions, evidenced by publications or patents.
Leadership experience overseeing global research teams across multiple time zones.
Knowledge of ARM chipset and its ecosystem is a bonus.
Responsibilities
Conduct comprehensive analysis of advanced technologies and mainstream products in the data field.
Lead innovation in big data engines, data-AI integrations, and co-design of technologies for diverse platforms.
Develop a strategic roadmap for 'Data+AI' technologies to ensure commercial viability of initiatives.
Oversee the development of high-caliber Data+AI solutions for modern data processing challenges.
Attract and manage top-notch talent within the data domain to build a leading research team.
Chair the Big Data Committee, guiding significant technical reviews and decisions.
Engage with industry and academia, utilizing open-source projects to promote the Kunpeng architecture.
Benefits
Opportunities for professional growth within a leading organization in the data and AI space.
Participation in cutting-edge projects that shape the future of data technology.
Access to a global network of industry experts and academic leaders.
Collaboration in a thriving open-source environment.
Leadership opportunities that influence significant advancements in technology.
Full Job Description
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.
