Huawei Canada has an immediate permanent opening for a Senior Researcher.
About the team:
The Computing Data Application Acceleration Lab aims to create a leading global
data analytics platform organized into three specialized teams using innovative
programming technologies. This team focuses on full-stack innovations, including
software-hardware co-design and optimizing data efficiency at both the storage
and runtime layers. This team also develops next-generation GPU architecture for
gaming, cloud rendering, VR/AR, and Metaverse applications.
One of the goals of this lab are to enhance algorithm performance and training
efficiency across industries, fostering long-term competitiveness.
About the job:
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Collaborate with internal and external organizations to lead the design of
foundational model architecture for LLM/Code/Multimodal subfields by
breakthroughs in post-training and continual training. Develop a foundational
model with state-of-the-art performance and hardware efficiency, and
establish industry impact.
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Propose the technical requirements for large-scale distributed training and
inference infrastructures such as parallelization and operator fusion,
analyze the computational characteristics of typical architectures, and
ensure the accuracy and advancement of AI hardware & infrastructure
evolution.
About the ideal candidate：
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Experience in training and optimizing cutting-edge AI models/applications,
especially in training and deploying AI models at a scale of 10B+ parameters.
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Proficiency in the latest AI architecture (such as long-sequence,
reinforcement learning, multimodal, and agents). Deep understanding of AI
algorithm mechanisms.
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Solid command of the underlying implementation of AI frameworks (such as
PyTorch, vLLM, and SGLang), and mainstream distributed training and inference
techniques.
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Familiarity with AI chip architecture (such as GPU, NPU, and TPU).
Understanding of memory hierarchy and interconnect technologies is an asset.
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PhD preferred in AI architecture, computer architecture, or related fields.
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Solid publication records in the field of AI systems or chip design are an
asset.
