GPU-Accelerated Data Processing Solutions Architect | Equity Options

NVIDIA Gruppe; California (MO); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Solutions Architect for High-Performance Databases to research and develop techniques for GPU-accelerated databases and data analytics on modern architectures. You will collaborate with researchers and industry experts to optimize complex workloads and influence future hardware and software designs.

Key responsibilities include working with cross-functional teams to push data processing capabilities and collaborating with industry partners to extend NVIDIA’s product line.

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, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.

Responsibilities

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

Skills

C/C++ programming

CUDA GPU programming

CPU/GPU architecture

Data analytics knowledge

Communication skills

Education

Master's or PhD in CS/CE or related field

Tools

OpenACC

OpenMP

MPI

pthreads

TBB

Job description

NVIDIA is seeking a Solutions Architect for High-Performance Databases to research and develop techniques for GPU-accelerated databases and data analytics on modern architectures. You will collaborate with researchers and industry experts to optimize complex workloads and influence future hardware and software designs.

Key responsibilities include working with cross-functional teams to push data processing capabilities and collaborating with industry partners to extend NVIDIA’s product line.