CUDA Deep Learning Systems Engineer — Optimize AI at Scale

NVIDIA; Town of Texas (WI); On-site; USD 124,000 - 196,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in the United States is seeking an experienced software professional to advance CUDA and Deep Learning Systems initiatives. You will work at the intersection of high‑level DL frameworks and low‑level CUDA, aiming to maximize hardware performance on modern accelerators from single GPUs to clusters.

Join a research‑oriented team focused on model optimization, custom kernel development, and cluster‑scale AI systems design.

Qualifications

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent).
• 2+ years of relevant industry experience or equivalent academic experience after degree.
• 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 performance challenges of cluster-scale execution.
• 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
• Experience profiling and optimizing generative AI models and vision models, including diffusion models.
• Track record of initiative and willingness to deep-dive on problems across the stack.

Responsibilities

• Explore, research, and prototype novel systems optimizations for 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 for emerging neural network architectures.
• Analyze hardware-software interactions to identify 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 systems and algorithms.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.
• Write clean, maintainable code so prototypes can transition to open-source releases or production.

Skills

C++

Python

Deep Learning fundamentals

Distributed computing

CUDA programming

Transformers knowledge

Research experience

Education

BS/MS/PhD in CS/CE/EE

Tools

CUDA

NCCL

MPI

UCX

Triton

XLA/torch.compile

Job description

NVIDIA in the United States is seeking an experienced software professional to advance CUDA and Deep Learning Systems initiatives. You will work at the intersection of high‑level DL frameworks and low‑level CUDA, aiming to maximize hardware performance on modern accelerators from single GPUs to clusters.

Join a research‑oriented team focused on model optimization, custom kernel development, and cluster‑scale AI systems design.