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AI Research Engineer – Optical Networking

Job in Ottawa, Ontario, Canada
Listing for: Huawei Technologies Canada Co., Ltd.
Contract position
Listed on 2026-01-13
Job specializations:
  • Engineering
    AI Engineer, Systems Engineer
  • IT/Tech
    AI Engineer, Data Scientist, Machine Learning/ ML Engineer, Systems Engineer
Job Description & How to Apply Below

Job description

Huawei Canada has an immediate 12-month contract opening for an AI Research Engineer.

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:

  • Develop AI/ML models and agents for network optimization, routing and resource allocation.

  • Write Python code to implement new ideas or algorithms, troubleshoot and diagnose integration issues, and refine solutions.

  • Conduct simulations and experiments to validate efficacy of AI/ML models and evaluate their performance.

  • Prepare reports and present findings to technical and non-technical stakeholders.

  • Collaborate with cross-functional teams to embed AI into optical platforms.

  • Stay abreast of AI/ML advancements to come up with innovative solutions and apply them to optical network automation and optimization tasks.

  • Job requirements

    About the ideal candidate:

  • Master’s or PhD degree in Computer Science or Electrical Engineering.

  • Solid understanding of the concepts and familiarity with the technologies of optical communication and networking.

  • In-depth knowledge of AI/ML through some hands-on experience with Deep Neural Networks and Reinforcement Learning (RL).

  • Proficiency in Python, with proven ability to write efficient, scalable code, plus extensive experience with PyTorch.

  • Strong problem-solving and communication skills and a passion for tackling complex technical problems.

  • Familiarity with Graph Neural Networks (GNN) and neural combinatorial optimization techniques and architectures is an asset.

  • #LI-PB1

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