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Computing Network & System Architecture Group Leader

Toga NetworksHod Hasharon и ещё 1 городот 10 лет
AIDistributed systemsData CenterSystem ArchitectureHPCNetwork ProtocolsNetwork ArchitectureComputer NetworksRouting Algorithms

Описание

This role is for a Group Leader in the System & Network Architecture Team within Huawei's Computing Network Innovation Lab, focusing on next-generation computing network architecture research for AI and HPC data centers. The mission is to achieve differentiated competitiveness in high-performance computing cluster network infrastructure.

Responsibilities

  • Deeply analyzing the advantages and disadvantages of mainstream network systems to find opportunities for network architecture innovation
  • Insight into the technology developing trend of the high-performance computing network field and leading the corresponding technology planning
  • Exploring new architectures of high-performance computing network systems and efficiently integrating communication library, topology, and network protocol to solve performance bottlenecks
  • Analyzes computing cluster network performance and leads the development of computing cluster network technologies
  • Research and optimize the heterogeneous interconnection topology of key computing chips to continuously improve the key competitiveness of Huawei computing heterogeneous chipsets
  • Responsible for the research of data center network technologies and guide network topology design and routing algorithm development
  • Lead the development of a comprehensive system architecture for AI Fabric and HPC Fabric solutions
  • Manage and mentor highly skilled team leaders to ensure that the group operates together in pursuit of common goal
  • Foster a collaborative and innovative work environment
  • Provide technical guidance and support to team members
  • Collaborate closely with cross-functional teams internationally, including hardware, software, and ucode design teams, to ensure alignment of architectural decisions with product and platform common objectives
  • Initiate and supervise collaborations with top academic researchers in Israel and abroad
  • Stay up to date with emerging technologies and industry trends in AI, HPC and big data industries
  • Evaluate and recommend technologies and next generation projects
  • Occasional travel related to ongoing projects, seminars, conferences etc.

Requirements

  • At least 10 years of hands-on experience in system architecture design, or equivalent research experience
  • Demonstrated experience in leading R&D team
  • Familiarity with high-performance computing cluster services and system architectures, such as AI, HPC and big data
  • In-depth understanding of computer networks, communication libraries, and design of AI or HPC cluster networks
  • Ability to work in a team environment; actively seek out resolution to issues with the team and work co-operatively to build a coherent system
  • Team-working and excellent inter-personal communication skills
  • High level of self-reliance and an autonomous target-oriented work style, “can do” attitude, eager to learn new things and ready to think outside the box
  • Ability to work on a schedule, even for un-schedule-able issues such as inventiveness
  • Experience with network system of AI, HPC or big data cluster
  • Demonstrated capability in several items from the list below:
  • Deep understanding of computer network protocol and network topology of computing cluster
  • Familiarity with communication library, such as OpenMPI/NCCL
  • Extensive experience in leading the network architecture design of computing cluster
  • Experience with implementing routing algorithm
  • Familiarity with network specifications of CPU/Network Processing Unit/ Neural Processing Unit/Switch chip
  • Fluent in written and spoken English

Nice to have

  • You hold a Doctor’s degree or above in the field of computer science, electrical and electronic engineering or in a similar background in Research & Development
  • Publications in reputed journals and conferences