NVIDIA
GPU accelerated computing
SolutionsArchitect,DataProcessing
Neural analysis suggests this role is
optimal for Entry candidates.
“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.
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
Applying for this Solutions Architect, Data Processing role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about NVIDIA?
Real rants from real employees. Read before you apply.