Principal Researcher - Data Center Network

Company Overview

Huawei is a leading global information and communications technology (ICT) solutions provider. Through our constant dedication to customer-centric innovation and strong partnerships, we have established leading end-to-end capabilities and strengths across the carrier networks, enterprise, consumer, and cloud computing fields. Our products and solutions have been deployed in over 170 countries serving more than one third of the world’s population.

With 28 sites across Europe and 2000 researchers, Huawei’s European Research Institute (ERI) oversees fundamental and applied technology research, academic research cooperation projects, and strategic technical planning across our network of European R&D facilities. Huawei’s ERI includes the Zurich Research Center (ZRC), located in Zurich, Switzerland.

The research work of the lab will be carried out not only by Huawei’s internal research staff but also by our academic research partners in universities across Europe. The lab will provide an open research environment where academics will be encouraged to visit and work on fundamental long-term research alongside Huawei staff in an environment that, like the best universities and research institutes, is open and conducive to such world-leading scientific work.

In order to strengthen Data Center Network Lab, we are looking for a Principal Researcher – Data Center Network

In this role, you will be responsible for the research and set up the direction of DCN services and architecture, key DCN algorithms and protocols. You will also help the team to complete key technological innovations, and build key technical breakpoints.

Responsibilities

Conduct cutting-edge research on the next-generation Data Center Network architecture and new technologies
Collaborate with a wide range of colleagues and stakeholders: Huawei Researchers and Experts in Switzerland and around the world, Swiss and European Universities, and Huawei Product teams.
Develop and prototype novel Data Center Networking methods
Optimize the performance and efficiency of parallel computing systems, especially the large-scale AI clusters mainly from the perspective of the integration of network, computing, and storage systems
Identify technology trends in the field of Data Centre Networking
The scope includes but is not limited to network topology, traffic control technology, software-defined networks, optical and electrical hybrid networks, in-network computing, etc.

Requirements

PhD in Computer Science, Electronic Engineering, Artificial Intelligence, Automation, Mathematics, Physics and other relevant discipline.
At least 5 years of work experience in Data Center Network Research either in industry or academia.
Proficiency in data center networks and high-performance interconnection technology systems.
Sound experience in performance or efficiency optimization of parallel computing systems.
Strong knowledge in large-scale distributed deep learning and be familiar with corresponding infrastructure and key technologies.
Excellent communication skills in English, both written and verbal
Ability to engage with a multicultural team both locally and across multiple global sites
Team spirit with the ability to work independently

Candidates should have research experience and strong cross-domain knowledge in the following areas:

Modern network technology or high-performance interconnection, cloud DCN technologies, including network architecture, resource pooling techniques, optical network techniques, etc.
Performance or efficiency optimization of parallel computing systems. Research on distributed machine/deep learning, distributed storage, high-performance computing systems, including network architecture, networking solutions, and the design of new device forms.
Infrastructure and key technologies of large-scale training/inference combined with systematic thinking on how to improve the system scale and efficiency (Optional).
Network theory and optimization algorithms, focusing on DCN business service assurance technology, network congestion control, traffic scheduling/forecasting, TCP/RDMA acceleration, and low-latency assurance for DCN, etc.
New data center architectures, new topologies, new protocols, new hardware, and algorithms, such as CXL bus protocol extensions, non-CLOS topologies, GPU cluster interconnections, and DPU offloading, among other new technological directions