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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.
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.
