Job description
Huawei Canada has an immediate 12-month contract opening for an Engineer.
About the team:
The Big Data and Intelligence Platform lab is focused on advancing core AI technologies for the Cloud, utilizing large language models (LLMs) to tackle complex real-world challenges across various sectors. Composed of researchers with advanced degrees from top Canadian universities, this lab specializes in integrating LLMs for operations research, analytical databases, and data systems, optimizing efficiency within LLM architectures. This lab prioritizes responsible AI practices, including data watermarking and federated learning. Committed to academic excellence, findings are published in leading conferences, shaping the future of AI technology and contributing to the scientific community.
About the job:
Develop software targeted on Huawei's hardware; both fundamental kernels and cutting edge tools
Apply your parallel and high performance computing knowledge to improve performance of various aspects of our solver
Develop GPU/NPU versions of classical algorithms or new algorithms that can solve critical problems in applications
Improve training and inference performance of machine learning models on GPU/NPU.
Assist in profiling, bottleneck analysis, testing and validation
Assist teams to accelerate their software on Huawei's heterogenous architectures: CPU + X
Collaborate and communicate with team members to ensure smooth integration with the larger project
The target annual compensation (based on 2080 hours per year) ranges from $100,000 to $180,000 depending on education, experience and demonstrated expertise
Job requirements
About the ideal candidate:
Ph.D or Master's degree in Computer Science, Electronic Engineering, or related fields, or an equivalent level of proven work experience and successful project delivery
Experience in developing core algorithms for GPUs, TPUs, FPGAs or ASICs
Expert level C/C++ programming skills
Experience in high performance computing applications
Strong foundation of sparse computations, linear algebra and matrix computation
Familiarity with some performance profiling tools
Some knowledge of tools used in machine learning like torch, tensorflow, etc.
Experience with BLAS/LAPACK and well-known Sparse Linear Solvers is an asset
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