Senior Principal Researcher - AI Data Platform

About the role

Huawei Canada has an immediate permanent opening for a Senior Principal Researcher in the Emerging Storage Lab, a research group focused on next‑generation data and storage technologies. The role will define and drive the long‑term research agenda for AI‑native data platforms, including vector‑native data lakes, intelligent caching, and high‑performance retrieval for LLMs and RAG.

Key responsibilities

• 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.
• 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 an AI‑ready data stack.
• Publish groundbreaking research at top‑tier venues and secure patents for novel approaches.
• Represent the organization as a thought leader through speaking engagements and community participation.
• Collaborate with product and engineering teams to translate research into production‑ready systems.
• Mentor junior researchers and PhD interns, fostering a high‑impact research environment.

Required profile

• PhD in Computer Science, Information Retrieval, Data Management, or a related field.
• Minimum 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 for both academic and industry audiences.
• Ability to influence the field through publications, patents, and cross‑functional collaboration.

Required skills

• Milvus
• Pinecone
• Databricks
• Snowflake
• Vector databases
• Unstructured data processing
• Metadata enrichment
• Hybrid search