Database Research Scientist

Role overview A research-focused position on an applied research team that partners with engineering groups to push the state of the art in open-source database systems. The work spans query optimization, execution engines, distributed data management, indexing, materialized views, benchmarking, and emerging agentic workloads, with an emphasis on turning research ideas into production-quality improvements.

Responsibilities - Conduct applied research to improve the performance, scalability, reliability, and functionality of open-source database management systems. - Design and evaluate new algorithms, data structures, and architectures across query planning, indexing, storage, execution, and distributed coordination. - Build research prototypes and production-grade implementations, partnering with engineering teams to integrate successful techniques into widely used open-source systems. - Analyze large-scale workloads, performance traces, benchmarks, and telemetry to surface bottlenecks and optimization opportunities. - Design rigorous experiments and benchmarks that reflect realistic workloads, deployment environments, and hardware configurations. - Publish results through technical reports, open-source contributions, internal presentations, and submissions to leading systems and database venues.

Requirements - Ph.D. in Computer Science, Data Science, or a related field, with research experience in databases, distributed systems, systems software, or machine learning systems. - Strong publication record in peer-reviewed venues such as SIGMOD, VLDB, SOSP, OSDI, NSDI, or NeurIPS on database- or systems-related topics. - Hands-on programming background with database internals or comparable large systems codebases (for example PostgreSQL, MySQL, or a modern columnar DBMS). - Proficiency in systems programming using C, C++, Rust, Zig, or a comparable low-level language. - Strong analytical, experimental, and problem-solving skills, with the ability to communicate complex technical work clearly.

Nice to have - Experience developing or operating database systems on major cloud platforms such as AWS, Google Cloud, or Microsoft Azure. - Familiarity with large language models, reinforcement learning, or learned optimization applied to systems. - Prior contributions to large open-source projects, especially database engines, compilers, or storage systems. - Exposure to verification tooling such as TLA+/PlusCal, Alloy, or Lean, and to development tools like LLVM, eBPF, Go, Python, or advanced profilers and sanitizers. - Track record of database optimization through hardware acceleration (GPU, FPGA, CXL) using frameworks like CUDA, SYCL, or ROCm.

Benefits and work setup - Fully remote-friendly, globally distributed organization with team members in over 25 countries. - Employer contributions toward healthcare coverage. - Equity grants for new team members. - Flexible time off in the US and generous paid leave in other countries. - One-time home office setup allowance for remote hires. - Periodic in-person company-wide gatherings to encourage cross-team collaboration.