Senior Principal Researcher - AI Data Platform
Huawei Technologies Canada Co., Ltd. Open · verified Oct 22, 2026 At a glance
Senior AI Research role at Huawei Technologies Canada Co., Ltd. Markham · full-time · no salary stated · we estimate CA$151,100–CA$175,975 across Canada.
Huawei Technologies Canada Co., Ltd. has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the long-range research direction for AI data platforms, including vector data lakes, caching and retrieval for LLMs and RAG
- Develop research on agent memory, knowledge bases, dynamic indexing, hybrid search and keeping retrieved context current
- Prototype architectures that bring file storage, data lakes and fast vector indexes into one AI-ready platform
- Publish at leading research venues, pursue patents and share findings with academic and industry audiences
- Work with product and engineering teams to move research into production, while mentoring junior researchers and PhD interns
What you bring
- A PhD in computer science, information retrieval, data management or a related discipline
- At least three years researching data systems, information retrieval or AI/ML infrastructure
- A publication record at leading venues such as VLDB, SIGIR or NeurIPS
- Practical knowledge of hybrid search, index freshness, vector-space multi-tenancy and cost versus latency trade-offs
- Hands-on work with unstructured data, metadata enrichment, vector databases or data lakes
Who this fits
This senior research role suits someone who can publish and patent original work, explain technical ideas to academic and industry audiences, and collaborate across research, product and engineering. The position is based onsite in Markham.
From the employer
Huawei Canada has an immediate permanent opening for a Senior Principal Researcher.
About the team:
The Emerging Storage Lab is a research group based at Huawei Canada's Toronto Research Centre that is focused on next-generation data and storage technologies and innovations. Our team comprises graduate computer engineers and computer scientists with diverse industry experience, ranging from 0 to over 20 years. This lab investigates various data storage-related topics, including data management, data catalog, data fabric, file systems, storage networks, and AI storage, aiming to advance the field and drive data storage technological progress in the new AI era.
About the job:
Define and drive the long-term research agenda for AI-native data platforms, focusing on vector-native data lakes, intelligent caching, and high-performance retrieval infrastructures for LLMs and RAG.
Pioneer research in Agent memory systems, Knowledge Bases, and RAG-optimized data intelligence, advancing the field of Data-Centric AI.
Lead research in dynamic data indexing, hybrid search (semantic + keyword), intelligent chunking/parsing strategies, and real-time context freshness.
Design and prototype next-generation architectures that unify file storage, data lakes, and low-latency vector indexes into a cohesive, AI-ready data stack.
Publish groundbreaking research at top-tier venues (e.g., VLDB, SIGIR, NeurIPS, SIGMOD) and secure patents for novel approaches.
Represent the organization as a thought leader through speaking engagements and active participation in the academic and industry community.
Collaborate with product and engineering teams to translate research into production-ready systems with tangible real-world impact.
Mentor junior researchers and PhD interns, fostering a collaborative, high-impact research environment.
About the ideal candidate:
PhD in Computer Science, Information Retrieval, Data Management, or a related field.
3+ years of research experience in data systems, information retrieval, or AI/ML infrastructure.
Proven track record of publishing at top-tier venues such as VLDB, SIGIR, NeurIPS, SIGMOD, or ICDE.
Strong understanding of AI Data Platform challenges: hybrid search tuning, index freshness, multi-tenancy in vector spaces, and cost/latency trade-offs.
Hands-on experience with unstructured data processing, metadata enrichment, vector databases (e.g., Milvus, Pinecone), or Data Lakes (e.g., Databricks, Snowflake).
Exceptional communication skills with the ability to articulate complex research concepts to both academic and industry audiences.
Proven ability to influence the field through publications, patents, and cross-functional collaboration across research, product, and engineering.
Additional Information:
Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know and we will work with you to meet your needs.
All applications for this position are reviewed directly by our hiring team, we do not use artificial intelligence tools to screen or select candidates.