About the Team We are the Infrastructure System Lab — a hybrid research and engineering group building the next-generation AI-native data infrastructure. Our work sits at the intersection of databases, large-scale systems, and AI. We drive innovation across:
- Next-generation databases: We build VectorDBs and multi-modal AI-native databases designed to support large-scale retrieval and reasoning workloads.
- AI for Infra: We leverage machine learning to build intelligent algorithms for infrastructure optimization, tuning, and observability.
- LLM Copilot: We develop LLM-based tooling like NL2SQL, NL2Chart.
- High-performance cache systems: We develop a multi-engine key-value store optimized for distributed storage workloads. We're also building KV caches for LLM inference at scale. This is a highly collaborative team where researchers and engineers work side-by-side to bring innovations from paper to production. We publish, prototype, and build robust systems deployed across key products used by millions.
Job Responsibilities:
- Research cutting-edge technologies in the field of data management and security.
- Participate in the design and development of innovative data management and security projects, provide technical architecture and implementation plans based on performance, stability, scalability, and security considerations.
- Submit high-quality code and complete development tasks on time according to project schedules.
- Publish papers in top academic conferences (e.g., SIGMOD, VLDB, CCS).
Requirements
Minimum Qualification:
- Master's degree or higher in Computer Science or a related field, with a solid foundation in data structures and databases.
- Familiarity with Unix/Linux operating systems and proficiency in mainstream programming languages such as C/C++, Go, and Java; strong programming skills and habits.
- In-depth knowledge of database principles and understanding of common solutions and techniques for data security and privacy protection.
- Strong logical reasoning and the ability to quickly learn new technologies; excellent problem-solving skills and a strong sense of responsibility.
- Have published papers in accredited academic conferences (e.g., SIGMOD, VLDB, CCS).
Preferred Qualifications:
- Research experience in the intersecting areas of security, AI/LLM, and data management is preferred.
- Experience in the development of relational databases, NoSQL, or blockchain cores.
- Knowledge of blockchain principles and technologies such as Bitcoin, Ethereum, Libra, Hyperledger Fabric, etc.
- Understanding of the principles and components of blockchain database systems, such as QLDB, LedgerDB, Oracle Blockchain Table, Microsoft SQL Ledger, etc.
- Proficiency in common encryption and decryption algorithms, authentication and signature algorithms, hash algorithms, security protocol design, access control models, software security theories, etc.
- Research and practical experience in the security field, including but not limited to Trusted Execution Environment (TEE), secure multi-party computation, differential privacy, homomorphic encryption, threshold cryptography, function encryption, searchable encryption, zero-knowledge proofs, security proofs for protocol constructions, and cryptographic applications in blockchain.
- Preference for candidates with experience in optimizing cryptographic algorithms, implementing cryptographic libraries, large-scale cryptographic applications, or winners of programming competitions.