Researcher – ML/AI in Optical Communication

Huawei Canada has an immediate permanent opening for a Researcher.

About the Team:

Huawei Canada's Advanced Optical Technology Lab focuses on advanced R&D in high-performance optical communications and networking. Our expert team specializes in transmission algorithms, systems, physics, and optical network management. The lab engages in projects ranging from deep research to developing key product features, actively participating in standards organizations and collaborative research with partners. Our multicultural environment fosters innovation, mentorship, and a passion for learning. If you thrive on solving complex technical challenges, this lab is your ideal place.

About the Job:

• Responsible for developing and deploying AI tools that analyze data from optical communication systems, identify potential issues, and create precise and efficient models that leverage our expertise in physical modeling.

• Write technical documents and participate in internal technical sharing and external academic exchanges.

• Lead or participate in cross-department projects to promote the wide application of AI technologies in the optical communication field.

Requirements

About the ideal candidate:

• Master's degree or PhD in Computer Science, Electrical Engineering, Communications Engineering, or related fields.

• Deep understanding of the mathematical models behind AI algorithms and a strong passion for applying AI to solve complex problems in optical communication systems.

• Proficient in Machine Learning (ML) and Deep Learning (DL) algorithms, such as regression, classification, clustering, neural networks (CNN, RNN, GAN, etc.). Deep understanding of the mathematical models and principles behind algorithms, such as linear algebra, probability statistics, optimization algorithms, etc. Understanding of MoE is an asset.

• Capable of selecting appropriate algorithms and making improvements and optimizations based on specific problems and data characteristics.

• Familiar with mainstream AI frameworks and tools, such as TensorFlow, PyTorch, Keras, etc. Knowledgeable in model compression, acceleration, and optimization techniques to enhance model efficiency and performance.

• Proficient in data science programming languages such as Python, C/C++, Julia, etc. Familiar with data processing and analysis tools, such as NumPy, Pandas, Matplotlib, etc.

• Strong communication and teamwork skills. Able to effectively communicate with system and hardware engineers, understanding business requirements and technical details.

• Knowledge in optical communication,  experience in physical modeling and simulation, capable of integrating physical models with AI models, familiar with experimental design methods, able to analyze experimental data and draw conclusions is an asset.  

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