Senior Principal Engineer - Cognitive Enhancement for Foundation Model Applications
Job Description
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:
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.
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.
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.
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:
Ph.D. in Computer Science, AI, Machine Learning, or a related field, ideally with post-graduation experience in industry LLM applications.
Solid foundation in algorithms and programming, with proficiency in at least one of Python, Java, C++, or Go.
Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and LLM platforms such as Langchain, Dify, or similar.
Proven experience in one or more areas: foundation models, search/recommendation systems, graph reasoning, or advanced search algorithms (e.g., heuristic methods).
Strong problem-solving skills, team collaboration ability, and intellectual curiosity toward emerging technologies.
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