Senior GPU-Accelerated Database Engineer

NVIDIA Corporation; New York (NY); Hybrid; USD 184,000 - 288,000; Full time

Job summary

NVIDIA Corporation in the United States seeks a Senior Developer Technology Engineer for High-Performance Databases to explore GPU-accelerated techniques and memory management improvements. You will work with researchers and engineers to optimize data-intensive workloads on modern architectures and influence future hardware and software designs.

You will publish findings at conferences and blogs, collaborate across hardware, software, and libraries teams, and contribute to advancing NVIDIA's

Qualifications

• Master's or PhD in Computer Science, Computer Engineering, or related computation-focused field.
• 5+ years of relevant work or research experience.
• Proficiency in C/C++ and solid understanding of algorithms.
• Hands-on experience with low-level parallel programming: CUDA, OpenACC, OpenMP, MPI, pthreads, TBB.
• In-depth CPU/GPU architecture knowledge, particularly memory subsystems.
• Domain expertise in high performance databases, ETL and data analytics.

Responsibilities

• Research and develop GPU-accelerated techniques for high-performance databases and ETL applications.
• Collaborate with researchers and engineers to optimize complex data workloads on NVIDIA architectures.
• Influence the design of next-generation hardware, software, and programming models across teams.
• Publish findings through developer blogs and at conferences/workshops.

Skills

C/C++

Algorithms

Parallel programming

Education

Master's or PhD in Computer Science/Computer Engineering

Tools

CUDA

OpenACC

OpenMP

MPI

pthreads

TBB

Job description

NVIDIA Corporation in the United States seeks a Senior Developer Technology Engineer for High-Performance Databases to explore GPU-accelerated techniques and memory management improvements. You will work with researchers and engineers to optimize data-intensive workloads on modern architectures and influence future hardware and software designs.

You will publish findings at conferences and blogs, collaborate across hardware, software, and libraries teams, and contribute to advancing NVIDIA's