Huawei Canada has an immediate 12 month opening for a Researcher.
About the Job:
• 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.
The targeted annual total compensation (based on 2,080 hours per year) ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.
About the ideal candidate:
• 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; Past publications, patents, or open-source contributions in databases, distributed systems, AI infrastructure, or related areas is an asset.
• 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.
