Senior Solutions Architect – GPU-Accelerated Data Processing

NVIDIA; United States; On-site; USD 224,000 - 357,000; Full time

Job summary

NVIDIA is seeking a Solutions Architect for High-Performance Databases to research and develop techniques to GPU-accelerate database, ETL and data analytics workloads on modern architectures.

You will collaborate with experts across research, hardware, system software, libraries and tools teams to optimize data-intensive workloads, influence future hardware designs, and engage with industry and academia to push the boundaries of data processing using NVIDIA’s product lines.

Qualifications

• Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.
• 8+ years of experience.
• Programming fluency in C/C++ with a deep understanding of algorithms and software design.
• Hands-on experience with low-level parallel programming (CUDA preferred) and related frameworks.
• In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
• Domain expertise in high performance databases, ETL and data analytics and/or vector database.
• Good communication and organization skills with a logical approach to problem solving and prioritization.

Responsibilities

• Research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications.
• Work with technical experts to analyze and optimize data-intensive workloads for GPU architectures.
• Influence the design of next-generation hardware architectures, software and programming models.
• Influence partners to push the bounds of data processing with NVIDIA’s product line.

Skills

C/C++ programming

CUDA

CPU/GPU architecture knowledge

Data analytics / ETL knowledge

Communication and organization

Education

Masters or PhD in CS/CE or related field

Tools

CUDA

OpenACC

OpenMP

MPI

pthreads

TBB

Job description

NVIDIA is seeking a Solutions Architect for High-Performance Databases to research and develop techniques to GPU-accelerate database, ETL and data analytics workloads on modern architectures.

You will collaborate with experts across research, hardware, system software, libraries and tools teams to optimize data-intensive workloads, influence future hardware designs, and engage with industry and academia to push the boundaries of data processing using NVIDIA’s product lines.