Senior Researcher – AI Data Systems
About The Position
Huawei Canada has an immediate 12 month opening for a Researcher. The Distributed Scheduling and Data Engine Lab is Huawei Cloud's technical innovation center in Canada, focusing on researching and developing advanced cloud technologies. Current research areas include cloud native databases, intelligent SQL engine, LLM/Agent infrastructure and LLM/Agent Evaluation Technology. The lab fosters a robust technical environment, allowing collaboration with industry experts to create a highly competitive cloud platform. This role involves researching, designing, and prototyping next-generation data systems for AI applications, including LLMs, AI agents, RAG systems, and multimodal workloads. Responsibilities include designing scalable architectures for agent memory, semantic retrieval, vector search, knowledge management, and AI data lifecycle management. The researcher will investigate and evaluate state-of-the-art technologies in various database and distributed systems fields, develop proof-of-concept systems, explore advanced capabilities, review research from top conferences, and collaborate with engineers and researchers to translate innovative ideas into product-ready technologies. Contributions to invention disclosures, patent applications, technical reports, and publications are also expected.
Requirements
- Strong programming skills in C++, Rust, Go, or related systems programming languages
- Experience with systems-level software development, performance optimization, debugging, and distributed systems.
- Understanding of modern AI applications such as LLMs, RAG pipelines, AI agents, semantic search, or vector retrieval systems.
- Familiarity with cloud-native technologies, distributed storage, parallel computing, consistency protocols, and large-scale system architecture
- Experience with database internals such as storage engines, query processing, indexing, transaction management, concurrency control, and distributed databases.
- Strong research mindset with the ability to quickly learn new technologies, analyze academic literature, and prototype innovative ideas.
- Familiarity with PostgreSQL or other open-source database systems and their internal architecture.
- Experience with vector databases, graph databases, knowledge graphs, or AI data infrastructure technologies.
- Experience developing database extensions or AI-related data system components (e.g., pgvector, Apache Arrow, Spark, DuckDB, Milvus, Weaviate, LanceDB, or similar technologies).
- Experience leveraging modern hardware accelerators such as GPUs, NPUs, TPUs, or other heterogeneous computing platforms.
- Master’s or Ph.D. degree in Computer Science, Computer Engineering, Mathematics, or a related discipline.
Nice To Haves
- Past publications, patents, or open-source contributions in databases, distributed systems, AI infrastructure, or related areas is an asset.
Responsibilities
- Research, design, and prototype next-generation data systems that support AI applications, including LLMs, AI agents, RAG systems, and multimodal workloads.
- Design scalable architectures for agent memory, semantic retrieval, vector search, knowledge management, and AI data lifecycle management.
- Investigate and evaluate state-of-the-art technologies in vector databases, graph databases, data lake houses, retrieval systems, distributed storage, and cloud-native infrastructure.
- Develop proof-of-concept systems and production-quality components using modern database technologies and distributed systems principles.
- Explore advanced capabilities including: Vector search and similarity retrieval, Agent memory systems, Knowledge graph integration, Semantic indexing and retrieval, Hybrid transactional and analytical processing for AI workloads, AI-driven query optimization and autonomous database capabilities.
- Review and summarize recent research from top conferences such as SIGMOD, VLDB, CIDR, ICDE, OSDI, SOSP, NeurIPS, ICML, and ICLR.
- Collaborate with engineers and researchers to translate innovative ideas into product-ready technologies.
- Contribute to invention disclosures, patent applications, technical reports, and publications in leading academic and industrial venues.
Benefits
- Fair, inclusive, and accessible recruitment process
- Accommodation during the hiring process
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What This Job Offers
Job Type
Full-time
Career Level
Senior
