This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Conduct research and develop methods to enhance the performance of high-performance databases, ETL, and data analytics applications using GPU acceleration.

• Collaborate directly with technical experts from both industry and academia to carry out comprehensive analysis and optimization of intricate data-intensive tasks.

• Improve performance for existing GPU architectures.

• Shape the design of future hardware architectures, software, and programming paradigms.

• Partner with research, hardware, system software, libraries, and tools teams at NVIDIA.

• Drive advancements in data processing through collaboration with industry and academic partners utilizing NVIDIA’s product offerings.

⛳️ Requirements

• A Master’s or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent professional experience.

• Over 8 years of relevant experience.

• Proficient in programming with C/C++ and possess a thorough understanding of algorithms and software design principles.

• Practical experience with low-level parallel programming, such as CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.

• Extensive knowledge of CPU/GPU architecture fundamentals, particularly in memory subsystems.

• Specialized knowledge in high-performance databases, ETL processes, data analytics, and/or vector databases.

• Strong communication and organizational skills, with a logical mindset for problem-solving and prioritization.

• Experience in optimizing or implementing database operators or query planners, particularly within parallel or distributed frameworks (e.g., production databases or Spark).

• Familiarity with optimizing vector database index creation and/or search functions.

• Experience in profiling and enhancing CUDA kernels.

• Background in compression, storage systems, networking, and distributed computing architectures.