GPU AI Acceleration Research Intern

NVIDIA; West of England; On-site; GBP 32,000 - 42,000; Full time

Job summary

NVIDIA is seeking a research-oriented candidate in the UK to explore techniques for GPU-accelerated workloads in deep learning and AI domains. You will collaborate with industry and academia to analyze and optimize complex AI/HPC algorithms for modern CPU and GPU architectures.

You will publish findings, present at conferences, and help shape future hardware and software design, working with cross-functional teams across research, hardware, system software, libraries, and tools.

Qualifications

• Currently pursuing a PhD or Master degree in Computer Science, Computer Engineering, or related computationally focused science degree.
• Programming fluency in C/C++ with a deep understanding of algorithms and software development.
• Background in parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads, etc.).
• Strong communication, organization, and problem-solving skills.

Responsibilities

• Research and develop techniques to GPU accelerate workloads in deep learning, ML or AI domains.
• Collaborate with experts in industry and academia for in-depth analysis and optimization of AI/HPC algorithms.
• Publish and present optimization techniques in blogs or conferences to educate the developer community.
• Influence design of next-generation hardware architectures, software, and programming models.

Skills

C/C++

Algorithms

Communication

Education

Master's or PhD candidate in Computer Science/Computer Engineering

Tools

CUDA

OpenMP

MPI

OpenACC

Job description

NVIDIA is seeking a research-oriented candidate in the UK to explore techniques for GPU-accelerated workloads in deep learning and AI domains. You will collaborate with industry and academia to analyze and optimize complex AI/HPC algorithms for modern CPU and GPU architectures.

You will publish findings, present at conferences, and help shape future hardware and software design, working with cross-functional teams across research, hardware, system software, libraries, and tools.