Senior Researcher - AI Data Platforms

About the role

Huawei Canada’s Emerging Storage Lab is seeking a Senior Researcher to lead applied research on next‑generation AI‑driven data storage and retrieval systems. The role focuses on vector‑native data lakes, intelligent caching, and high‑performance Retrieval‑Augmented Generation (RAG) infrastructure.

Key responsibilities

• Conduct applied research on AI data storage, including vector‑native data lakes, intelligent caching, and petabyte‑scale RAG systems.
• Pioneer work on Agent memory systems, Knowledge Bases, and hybrid search techniques.
• Design and prototype unified architectures for file storage, data lakes, and vector indexes with robust lineage and versioning.
• Optimize distributed data planes for fast checkpointing, model/KV cache loading, and low‑latency metadata serving.
• Develop system software that integrates AI storage, data preparation, and orchestration frameworks such as Ray, Kubernetes, and Slurm.
• Publish research at top‑tier conferences and contribute to patents and industry forums.

Required profile

• Ph.D. or Master’s in Computer Science or related field with a strong research background in data management, storage systems, or AI/ML infrastructure.
• Demonstrated expertise in RAG, Agent memory, or vector databases through first‑author publications at top conferences.
• Experience building and prototyping large‑scale systems, preferably with C/C++ and Python.
• Solid understanding of storage architectures (object stores, distributed file systems, caching layers) and retrieval challenges.
• Familiarity with AI/ML development lifecycles, including data drift, distributed loading, and advanced RAG techniques.

Required skills

• C/C++
• Python
• Distributed storage APIs (S3, HDFS, POSIX)
• Vector indexing libraries (FAISS, ScaNN)
• Ray, Kubernetes, Slurm
• NVMe, RDMA, async I/O