Job Title: Researcher - AI Data System
About the Team: Cloud Native Data Engine team within Distributed Scheduling and Data Engine Lab, led by esteemed technical experts with extensive industry and academic experience, merge software development with cutting-edge industrial research in cloud database area. Our research currently focuses on cloud native database architecture (TaurusDB) and high-performance query and transaction processing (SQL Engine) in next-generation cloud infrastructure. Team publishes innovative research at leading conferences SIGMOD, VLDB, ICDE and recognized as key technology contributors in industry.
About the Job:
- This unique role combines software development with cutting-edge industrial research in databases, encompassing cloud-native database architecture (TaurusDB) and high-performance query and transaction processing (GaussDB SQL Engine) within next-generation cloud infrastructure.
- Design, implement, and maintain database architectures for machine learning workloads, ensuring efficient data management and optimized performance.
- Research and stay updated on emerging trends in database technology and machine learning to propose innovative solutions that improve system efficiency and capability.
- Investigate and summarize state-of-the-art database technologies by reviewing the latest conference papers, attending workshops, and engaging with industry trends.
- Assist in the implementation of AI-driven analytics and advanced features like vector search, similarity matching, and recommendation systems.
- Actively pursue opportunities to invent and submit patents, as well as write papers in leading academic and industrial conference. About the ideal candidate:
- 1-3 years of strong programming skills in C/C++, with expertise in systems-level programming and debugging.
- Deep understanding of cloud computing technologies, including cloud storage, distributed systems, parallel computing, and consistency protocols.
- Experience working with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and understanding how they can be applied within database contexts.
- Familiarity with MySQL, PostgreSQL, or other open-source databases — including knowledge of their internal mechanisms such as transaction management, storage engines, MVCC, SQL optimization, query execution, and vector execution — is considered an asset.
- Familiarity with AI agents and practical experience in deployment, or experience integrating ML models into production databases or data pipelines, is considered an asset.
- Experience with database extensions or ML-related plugins (e.g., pgvector for PostgreSQL); Preferably using modern AI accelerators, such as GPUs, NPUs, or TPUs.
- Proven ability to conduct research and quickly learn new technologies and products.
- A master’s or Ph.D. in Computer Science, Computer Engineering, Mathematics, or a related field is an asset.
If you’re excited about pushing the boundaries of AI-enhanced databases and cloud systems in a collaborative, research-driven environment, we’d love to hear from you. You can reach out to us directly for more details.
Company: Huawei Canada Technologies. Name: Kelly Wang (Technical Recruiter) Email: kelly.jia.wang1@huawei.com LinkedIn: Kelly Wang | LinkedIn
