NVIDIA

GPU accelerated computing

SolutionsArchitect,DataProcessing

$124–242k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“Solutions Architect, Data Processing at NVIDIA. Skills: GPU-accelerate high performance database, ETL and data analytics applications, Analyze and optimize complex data intensive workloads, Influence the design of next-generation hardware architectures, software, and programming models, Push the bounds of data processing with NVIDIA’s full product line. Research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications. Perform in-depth analysis and ”

What You'll Achieve.

Accelerate databases on modern computer architectures; Optimize performance of data intensive applications; Ensure the best possible performance of current GPU architectures

Industry & Context.

GPU accelerated computing
Problems you'll solve

Logical approach to problem solving

What They're Looking For.

Must Have

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, In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem, Domain expertise in high performance databases, ETL, data analytics and/or vector database

Nice to Have

CUDA, Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark), Background in optimizing vector database index build and/or search, Experience profiling and optimizing CUDA kernels, Background with compression, storage systems, networking, and distributed computer architectures

What You'll Do.

Research and develop techniques to GPU-accelerate high performance database

ETL and data analytics applications

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

and programming models

Influence partners (industry and academia) to push the bounds of data processing with NVIDIA’s full product line

How You'll Work.

Team & Collaboration

Work directly with other technical experts in their fields (industry and academia); Collaborate with research, hardware, system software, libraries, and tools teams at NVIDIA; Influence partners (industry and academia)

Communication Scope

Good communication skills

Full Job Description

Would you enjoy researching new algorithms and memory management techniques to accelerate databases on modern computer architectures? Do you like investigating hardware and system bottlenecks, and optimizing performance of data intensive applications? Are you excited about the opportunity to work on the top tier edge of technology with both visibility and impact to the success of a leader like NVIDIA? If so, the Solution Architecture Team invites you to consider this opportunity. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Join our team with varied strengths today! **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 * Influence partners (industry and academia) to push the bounds of data processing with NVIDIA’s full product line **What we need to see:** * 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 algori

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