Intern Researcher - Computer Network and Protocol
Huawei Technologies
Job description
Huawei Canada has an immediate internship opening for a Researcher.
About the team:
The Distributed Data Storage and Management Lab leads research in distributed data systems, aiming to develop next-generation cloud serverless products that encompass core infrastructure and databases. This lab addresses various data challenges, including cloud-native disaggregated databases, pay-by-query user models, and optimizing low-level data transfers via RDMA. Teams within this lab create advanced cloud serverless data infrastructure and implement cutting-edge networking technologies for Huawei's global AI infrastructure.
About the job:
Explore, develop and eventually deploy state-of-the-art networking technologies and protocols for Huawei's global AI infrastructure, cloud and data-center networks, delivering innovations and performance to forge product competitiveness.
Explore new opportunities with understanding of the company/product line strategies and industry development trends and identification of business problems and core challenges, orchestrating research and technologies across the research and business scene into a single, cohesive technical road-map.
Maintain effective communication with professionals in both academia and industry and ensure Huawei’s value is being delivered.
Job requirements
About the ideal candidate:
In pursuit of Master, or PhD degree in Computer Science, Machine Learning, or related technical fields.
Proficiency in C++ and Python.
3+ years of academic/professional experience in research, or engineering and technical innovation.
Expertise in AI infrastructure, HPC or data-center networking technologies, including but not limited to; RDMA, network protocol stack optimization, collective communication scheduling, traffic engineering/routing, congestion control, topology design and resource allocation.
Experience in networking, data network architectures, software architecture, and distributed systems.
Demonstrated influence on networking technologies, in academia or industry context.
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