Huawei Canada has an immediate permanent opening for an Engineer.
About the team:
The Advanced Computing and Storage Lab, currently a part of the Vancouver
Research Centre, aims to explore adaptive computing system architectures to
address the challenges posed by flexible and variable application loads in the
future. It assists in ensuring the stability and quality of training clusters,
constructs dynamic cluster configuration strategy solvers, and establishes
precision control systems to create stable and efficient computing power
clusters. One of the lab's goals is to focus on key industry AI application
scenarios such as large model training/inference, based on key technologies like
low-precision training, multi-modal training, and reinforcement learning,
responsible for bottleneck analysis and the design and development of
optimization solutions, thereby improving training and inference performance as
well as usability.
About the job:
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Aiming at key industry AI application scenarios such as large model
training/inference, based on key technologies such as low-precision training,
parallel strategy tuning, and training resource tuning, be responsible for
the bottleneck analysis of the AI software system on the Ascend platform and
the design and development of optimization solutions to improve training,
inference performance, and ease of use.
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Responsible for the design and development of optimization solutions for AI
training/inference systems. Combined with the requirements of AI algorithms
for the system, through architectural optimization in computing, IO,
scheduling, etc., build large-model AI training frameworks, operator
libraries, acceleration libraries and other software frameworks and
acceleration features to provide a foundation for the next generation of
architectural innovation.
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Grasp the latest research progress and technological trends in the fields of
AI computing cluster architecture design, training acceleration, and
inference acceleration in the industry and academia, and continuously improve
the competitiveness of AI computing cluster systems.
The base salary for this position ranges from $100,000 to $170,000 depending on
education, experience and demonstrated expertise
About the ideal candidate:
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Ph.D or Masters degree in Computer Science, Computer Engineering majors in
artificial intelligence, computer science, software, automation, electronics,
communications, robotics, etc.
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Familiar with the common model structures of large models such as Deepseek
and Llama, and have basic technical accumulation in large model training and
inference optimization in the fields of LLM, MoE, multimodality, etc.
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Familiar with the hardware architecture and programming system of AI
accelerators such as GPU/NPU, and have experience in optimizing AI systems
with coordinated software and hardware cores.
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Those with any of the following experience is an asset:
1) Solid programming foundation, familiar with Python/C/C++ programming
languages, good architecture design and programming habits
2) Ability to work independently and solve problems, good at communication,
willing to cooperate, keen on new technologies, good at summarizing and
sharing, and like hands-on practice
3) Experience in the development of AI training frameworks and AI reasoning
engines, or algorithm hardware and related experience is an asset
4) Strong research capabilities in new technologies and new architectures,
can quickly track and gain insights into the most cutting-edge AI
technologies in the industry, and lead the continuous leadership of system
architecture innovation.
