CUDA Deep Learning Systems Engineer – High-Performance Kernels

NVIDIA Corporation; Santa Clara (CA); On-site; USD 124,000 - 196,000; Full time

Job summary

NVIDIA is seeking an experienced software professional to work on pioneering initiatives at the intersection of CUDA and Deep Learning Systems in Santa Clara, CA. You will explore novel optimizations, design high-performance CUDA kernels, and help scale AI workloads from a single GPU to clusters.

You will collaborate with AI researchers, HW/SW architects, and kernel experts to improve accelerator compute utilization and memory bandwidth, while contributing to exploratory tools and potential

Qualifications

• BS, MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or related field (or equivalent experience).
• 2+ years of relevant industry experience or equivalent academic experience after degree achievement.
• Strong proficiency in C++ and Python programming.
• Solid background in the fundamentals of Deep Learning with a focus on transformers.
• Strong understanding of distributed computing principles, multi-node scaling, and cluster-scale execution.
• Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
• Familiarity with CUDA programming, kernel optimization, and workload profiling.

Responsibilities

• Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping.
• Architect and optimize distributed computing systems that scale from a single node to cluster-scale supercomputing environments.
• Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads.
• Analyze hardware-software interactions to resolve performance bottlenecks in training and inference pipelines.
• Collaborate with AI researchers, HW and SW architects, kernel and compiler authors, and CUDA driver experts to co-design systems and algorithms.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.

Skills

C++

Python

CUDA

Distributed computing

Kernel optimization

Performance profiling

ML frameworks

Multi-node scaling

Hardware knowledge

Education

BS/MS/PhD in CS/CE/EE

Tools

CUDA toolkit

NCCL

MPI

UCX

TensorRT

Triton

XLA

TorchScript

Job description

NVIDIA is seeking an experienced software professional to work on pioneering initiatives at the intersection of CUDA and Deep Learning Systems in Santa Clara, CA. You will explore novel optimizations, design high-performance CUDA kernels, and help scale AI workloads from a single GPU to clusters.

You will collaborate with AI researchers, HW/SW architects, and kernel experts to improve accelerator compute utilization and memory bandwidth, while contributing to exploratory tools and potential