Senior Software Engineer

5 days ago


Kingston, Ontario, Canada Huawei Technologies Canada Co., Ltd. Full time
About the Role

We are seeking a highly skilled Senior Software Engineer to join our team at Huawei Technologies Canada Co., Ltd. as a Senior Engineer - AI and Infrastructure Development. In this role, you will be responsible for designing, implementing, and assessing application programming APIs, frameworks, and runtime systems software for heterogeneous architectures.

Key Responsibilities
  • Research and Development: Conduct research and development on core infrastructure, tooling, and platforms to improve the productivity, quality, and efficiency of engineering and serving foundation model applications.
  • Design and Implementation: Design, implement, and assess application programming APIs, frameworks, and runtime systems software for heterogeneous architectures (e.g., GPU, NPU), familiar with machine learning systems or AI infrastructures.
  • Integration and Support: Support the integration process of novel software frameworks on in-house hardware platforms (e.g., performance modeling, analysis of future computing architectures, resource allocation and management, scheduling, fault tolerance and resiliency, communication and shared memory).
  • Collaboration and Innovation: Meet top industry and academic leaders and experts around the world, collaborate with top researchers and students, consult with Engineering teams across diverse domains, publish research papers in far-reaching and impactful areas, and submit patent applications for novel inventions.
Requirements
  • Education: Master or PhD Degree in Computer Science, Electrical & Computer Engineering, Machine Learning, or relevant domains.
  • Technical Skills: Solid experience with one or more of the following programming languages: Python/C/C++/Go; Familiarity with software development practices (version management, build management, CI/CD, debugging and profiling).
  • Machine Learning and AI: Solid understanding in any of these areas: Machine Learning and/or Deep Learning, Large Models Training and Finetuning (e.g., NLP/CV).
  • Model Training and Inference: Experience with mainstream model training and inference frameworks and tools (e.g., PyTorch, Tensorflow, PaddlePaddle, Oneflow, MindSpore, HuggingFace Transformer&Accelerate, DeepSpeed, Megatron, FasterTransformer, Triton Inference).
  • Computer Architecture and Distributed Computing: Solid understanding in Computer Architecture, Distributed Computing, Parallel Computing, Cloud Native, Operating Systems, Networks; experience in using frameworks and tools of any of the aforementioned areas (e.g., Spark, Flink, Ray for Distributed Computing, Docker, K8S for Cloud-Native app/framework development).
  • Research and Communication: Ability to evaluate, apply, and mature published research to real-world problems on prototype systems.
  • Publications: Publications in related top-tier venues (e.g., ICSE, FSE, TSE, ICLR, ICML, NeurIPS, OSDI, SOSP) is an asset.


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