What you will be doing:
In this role, you will research and develop techniques to GPU-accelerate high performance database, ETL and data analytics 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
What we need to see:
Pursuing or recently completed Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.
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 (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
Domain expertise in high performance databases, ETL, data analytics and/or vector database.
Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.
Ways to stand out from the crowd:
Experienceoptimizing/implementingdatabase operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark).
Experience optimizing vector database index build and/or search.
Experience profiling and optimizing CUDA kernels.
Background with compression, storage systems, networking, and distributed computer architectures.
You will also be eligible for equity and .
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