Description
<div><p>Huawei Canada has an immediate 12-month contract opening for a Researcher.</p>
<h3>About the team:</h3>
<p>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.</p>
<p>One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.</p>
<h3>About the job:</h3>
<h3>Frontier AI Technology Research</h3>
<ul>
<li>Track the evolution of state-of-the-art AI model architectures, including Large Language Models (LLMs), Vision Language Models (VLMs), advanced attention mechanisms, and Mixture-of-Experts (MoE) architectures.</li>
<li>Analyze the computational characteristics of emerging model architectures and Agentic AI training and inference workloads.</li>
</ul>
<h3>Hardware-Oriented Workload Analysis</h3>
<ul>
<li>Develop a systematic framework to map AI applications and workloads to hardware requirements.</li>
<li>Identify key computational patterns, design efficient inference deployment strategies, and build analytical performance models.</li>
<li>Evaluate the impact of algorithmic and hardware innovations on system performance, and provide quantitative, explainable architectural recommendations for next-generation AI accelerators.</li>
</ul>
<p>The <b>total target annual compensation</b> (based on 2,080 hours per year) for this position ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.</p>
<br/>
<h3>About the ideal candidate：</h3>
<ul>
<li>Strong understanding of modern AI model architectures and emerging trends, including sparse attention, linear attention, Mixture-of-Experts (MoE), and related techniques.</li>
<li>Solid knowledge of AI accelerator architectures (e.g., GPUs, TPUs), with deep understanding of memory hierarchy, interconnect technologies, and hardware performance bottlenecks.</li>
<li>Hands-on experience with AI kernel development using technologies such as Triton, TileLang, CUDA, or equivalent. Strong understanding of FlashAttention and other state-of-the-art kernel optimization techniques.</li>
<li>Experience with modern LLM inference systems and optimizations, including vLLM, SGLang, or similar serving frameworks. Familiarity with the internals of deep learning frameworks such as PyTorch and JAX.</li>
<li>Experience using hardware performance analysis and profiling tools, with the ability to develop Roofline-based performance analysis methodologies and tools.</li>
<li>Ph.D. in Artificial Intelligence, Computer Architecture, Computer Systems, or a closely related field is an asset.</li>
<li>Demonstrated research contributions through publications or influential open-source projects in AI infrastructure, systems, or computer architecture is an asset.</li>
<li>Experience deploying and optimizing large-scale AI training or inference systems in production environments is an asset.</li>
</ul>
<h3>Additional Information:</h3>
<p>Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know and we will work with you to meet your needs.</p>
<p>All applications for this position are reviewed directly by our hiring team, <b>we do not use artificial intelligence tools</b> to screen or select candidates.</p></div>
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