Senior Software Engineer, CUDA Deep Learning Systems at NVIDIA

Department: Engineer, Sys SW

Compensation

$184,000 – $356,500/yr

Setup: Remote
Location: California · Austin, Texas · +1
Type: Full-time
Level: senior
Posted: Aug 31, 2026

Description

NVIDIA is hiring a CUDA and Deep Learning Systems Research Scientist to research, prototype, and optimize systems at the intersection of deep learning, CUDA, distributed computing, and accelerator hardware. The role involves custom kernel development, cluster-scale system architecture, performance analysis, runtime and profiling tool development, and collaboration with AI researchers and hardware and software architects. Candidates need a relevant advanced degree, 8+ years of relevant experience, strong C++ and Python skills, deep learning and transformer knowledge, and extensive CUDA and systems programming experience. The base salary is 184,000–287,500 USD for Level 4 and 224,000–356,500 USD for Level 5, with equity and benefits.

Required Skills

C++
Python
CUDA
Deep Learning
Distributed Computing
Systems Programming
Kernel Optimization
Performance Optimization
Transformers
NCCL

Additional Information

Minimum Education: Bachelor's, master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience
Required Previous Experiences: 8+ years of relevant industry experience or equivalent academic experience after degree achievement
Experience in systems programming, computer architecture, and low-level systems performance optimization
Hands-on CUDA programming, kernel optimization, and workload profiling
Experience profiling and optimizing generative AI models, including large language models
Research background in machine learning systems and experience optimizing vision, generative AI, or diffusion models
Preferred Qualifications: Deep expertise in deep learning framework performance internals and execution graphs
Experience with communication libraries and distributed machine learning techniques
Knowledge of numerical methods and low-precision arithmetic
Background in deep learning compilers and ML systems
Experience designing agentic AI systems for complex systems and infrastructure