NVIDIA is seeking to accelerate high-performance databases and ETL applications on modern computer architectures by researching new algorithms and memory management techniques, and optimizing data-intensive applications.
Requirements
- Programming fluency in C/C++ with a deep understanding of algorithms and software design.
- Hands-on experience with low-level parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, TBB, etc.
- In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
- Domain expertise in high performance databases, ETL and data analytics
- Experience optimizing the performance of distributed database systems and frameworks (e.g. production database or Spark).
- Background with compression, storage systems, networking, and distributed computer architectures.
Responsibilities
- research and develop techniques to GPU-accelerate high performance database and ETL applications.
- Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current GPU architectures.
- Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA
Other
- At least 5+ years of relevant work or research experience.
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.
- LI-Hybrid
