Senior GPU Databases DevTech Engineer Finance

Nvidia Corporation in; Santa Clara (CA); Hybrid; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Santa Clara invites applications for a Senior Developer Technology Engineer specializing in High-Performance Databases (Finance). In this role, you will research and develop techniques to GPU-accelerate database and ETL workloads, and collaborate with experts to optimize data-intensive tasks on current GPU architectures.

You will work with teams across research, hardware, system software, libraries and tools to influence next-generation architectures and programming models.

Qualifications

• Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
• At least 5+ years of relevant work or research experience.
• Fluency in C/C++ with deep understanding of algorithms and software design.
• Hands-on experience with low-level parallel programming (CUDA/OpenACC/OpenMP/MPI/pthreads/TBB).
• Deep knowledge of CPU/GPU architecture, memory subsystems.
• Domain expertise in high performance databases, ETL and data analytics.

Responsibilities

• Research and develop techniques to GPU-accelerate high performance databases and ETL applications.
• Collaborate with experts across industry and academia for in-depth analysis and optimization of data-intensive workloads.
• Influence design of next-generation hardware, software, and programming models with NVIDIA teams.

Skills

C/C++ programming

Parallel programming

CPU/GPU architecture

Education

Masters or PhD in CS/CE or related

Tools

CUDA

OpenACC

OpenMP

MPI

pthreads

TBB

Job description

NVIDIA Corporation in Santa Clara invites applications for a Senior Developer Technology Engineer specializing in High-Performance Databases (Finance). In this role, you will research and develop techniques to GPU-accelerate database and ETL workloads, and collaborate with experts to optimize data-intensive tasks on current GPU architectures.

You will work with teams across research, hardware, system software, libraries and tools to influence next-generation architectures and programming models.