Senior CUDA DL Systems Engineer - Performance & Kernels Equity

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

Benefits offered by this job

Equity

Benefits

Career growth

Job summary

NVIDIA is seeking an experienced software professional to work at the intersection of CUDA and Deep Learning Systems, exploring next-generation ideas that bridge deep learning and accelerator architectures.

Join a research-oriented team to optimize hardware performance for AI workloads, designing custom CUDA kernels, distributed systems, and profiling tools. This role emphasizes collaboration with AI researchers and HW/SW architects to enhance compute utilization across nodes and clusters.

Qualifications

• 8+ years of relevant industry experience or equivalent academic experience.
• 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.
• Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
• Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience 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 environments.
• Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads.
• Analyze hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines.
• Collaborate with AI researchers, HW/SW architects, kernel and compiler authors, and CUDA driver experts to co-design compute-efficient systems.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.
• Write clean, maintainable code, ensuring prototypes can translate into open-source releases or commercial products.

Skills

C++

Python

Deep Learning

Distributed computing

CUDA

Education

BS/MS/PhD in CS/CE/EE or related field

Tools

NCCL

MPI

UCX

Triton

XLA

Job description

NVIDIA is seeking an experienced software professional to work at the intersection of CUDA and Deep Learning Systems, exploring next-generation ideas that bridge deep learning and accelerator architectures.

Join a research-oriented team to optimize hardware performance for AI workloads, designing custom CUDA kernels, distributed systems, and profiling tools. This role emphasizes collaboration with AI researchers and HW/SW architects to enhance compute utilization across nodes and clusters.