Huawei Canada has an immediate permanent opening for a Senior Principal
Engineer.
About the team:
The Distributed Data Storage and Management Lab leads research in distributed
data systems, aiming to develop next-generation cloud serverless products that
encompass core infrastructure and databases. This lab addresses various data
challenges, including cloud-native disaggregated databases, pay-by-query user
models, and optimizing low-level data transfers via RDMA. Teams within this lab
create advanced cloud serverless data infrastructure and implement cutting-edge
networking technologies for Huawei's global AI infrastructure.
About the job:
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Innovation in Uncertainty Exploration: Drive cutting-edge research in areas
such as Deep Search and LLM-based cognitive enhancement. Apply multi-path
exploration and multi-stage experimentation across real-world scenarios to
create technical differentiation and support business innovation.
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Lead Technological Breakthroughs: Spearhead innovations across
retrieval-augmented generation (RAG), multi-agent collaboration, and related
AI technologies. Actively absorb and integrate the latest advancements from
academia and industry to address complex engineering challenges.
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Commercial Application & Productization: Translate research into robust,
scalable technologies powering Huawei’s cloud and device ecosystems.
Collaborate closely with product and platform teams to deliver impactful
developer tools and explore new business models driven by LLM capabilities.
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Ecosystem & Community Building: Take initiative in shaping the local AI
ecosystem by fostering cross-disciplinary collaboration with academia and
industry. Engage with conferences and communities focused on foundation
models, distributed systems, and knowledge retrieval.
About the ideal candidate:
The ideal candidate will be a highly successful and proven leader with strong
experience in leading foundation model enhancement, ideally in large global tech
environment. The successful candidate will have:
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Ph.D. in Computer Science, AI, Machine Learning, or a related field, ideally
with post-graduation experience in industry LLM applications.
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Solid foundation in algorithms and programming, with proficiency in at least
one of Python, Java, C++, or Go.
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Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
and LLM platforms such as Langchain, Dify, or similar.
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Proven experience in one or more areas: foundation models,
search/recommendation systems, graph reasoning, or advanced search algorithms
(e.g., heuristic methods).
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Strong problem-solving skills, team collaboration ability, and intellectual
curiosity toward emerging technologies.
