Senior Researcher - AI Data Platforms

Huawei Technologies Canada Co., Ltd.; Markham; On-site; CAD 127,000 - 225,000; Full time

Job summary

Huawei Canada seeks a Senior Researcher at its Toronto Research Centre to advance next‑gen AI data storage and retrieval systems, including vector-native data lakes and hybrid search architectures. The role emphasizes system prototyping, performance optimization, and collaboration with global teams.

Ideal candidates hold a Ph.D. or Master’s in CS with strong publication records in data management, AI infrastructure, or retrieval systems, and are proficient in C/C++ and Python.

Qualifications

• Ph.D. or Master's in Computer Science or related field with strong research.
• Deep research expertise in RAG, Agent memory, vector databases, or indexing tech.
• Proven systems-building and prototyping skills in C/C++ and Python.
• Familiarity with AI/ML lifecycles including LLM pre-training vs. fine-tuning.
• Excellent communication bridging hardware, software and AI disciplines.

Responsibilities

• Conduct applied research on next-gen AI data storage and retrieval systems.
• Pioneer research in Agent memory systems and RAG-optimized intelligence.
• Design and prototype data, metadata, and pipeline components with robust lifecycle management.
• Optimize the data plane for distributed shuffling, fast checkpointing, and low latency metadata serving.
• Develop system software integrating AI storage, data preparation, and orchestration frameworks.
• Optimize end-to-end data paths from storage to compute nodes across NVMe, RDMA and networks.
• Publish influential research and contribute to patents and forums.
• Collaborate with global teams on architecture reviews and strategic roadmap.

Skills

C/C++

Python

Distributed storage APIs (S3, HDFS,POS

Data processing frameworks

Vector indexing libraries (FAISS, ScaN

AI data storage

Education

Ph.D. or Master's in Computer Science or related field

Tools

Ray

Kubernetes

Slurm

FAISS

ScaNN

Job description

Huawei Canada has an immediate permanent opening for a Senior 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:

• Conduct applied research on next-gen AI data storage and retrieval systems, including vector-native data lakes, intelligent caching, and high-performance RAG infrastructure.
• Pioneer research in Agent memory systems, Knowledge Bases, and RAG-optimized intelligence, driving innovation in hybrid search, dynamic indexing, chunking/parsing, and real-time context freshness at petabyte scale.
• Design and implement data, metadata, and pipeline components with robust lineage, versioning, and lifecycle management, prototyping unified architectures for file storage, data lakes, and vector indexes.
• Optimize the data plane for distributed shuffling, fast checkpointing, model/KV Cache loading/offloading, and low-latency metadata serving for billion-scale entities.
• Develop system software integrating AI storage, data preparation, and orchestration frameworks (Ray, Kubernetes, Slurm), eliminating bottlenecks from curation to serving.
• Optimize end-to-end data paths from persistent storage to compute nodes, leveraging NVMe, RDMA, networking, prefetching, and async I/O to meet enterprise AI demands.
• Publish influential research on Agent Memory, RAG, and AI-native data management at top-tier conferences, and contribute to patents and industry forums.
• Collaborate with global research and engineering teams on architecture reviews, performance optimizations, and execution of the strategic roadmap.

The total target annual compensation for this position ranges from $127,000 - $225,000 depending on education, experience, and demonstrated expertise.

About the ideal candidate:

• Ph.D. or Master's in Computer Science or related field, with a strong research background in data management, information retrieval, storage systems, or AI/ML infrastructure.
• Deep research expertise in RAG, Agent memory, vector databases, or indexing technologies, demonstrated through first-author publications at top-tier conferences.
• Strong systems building and prototyping skills, with proficiency in C/C++ and Python, and experience with distributed storage APIs (S3, HDFS, POSIX), data processing frameworks, or vector indexing libraries (FAISS, ScaNN).
• Solid understanding of data storage architectures (object stores, distributed file systems, caching layers) and retrieval challenges including hybrid search, index freshness, and cost/latency trade-offs between dense and sparse methods.
• Familiarity with AI/ML development lifecycles, including data drift, distributed data loading, LLM pre-training vs. fine-tuning, and advanced RAG techniques (HyDE, Multi-Query, Contextual Compression).
• Excellent research communication skills, with the ability to articulate complex ideas across hardware, software, and AI disciplines, and a strong desire to bridge academic research with production-grade systems.

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.