NVIDIA

AI

SeniorSystemSoftwareEngineer-NeuralGraphicsPerformance

$152–288k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior System Software Engineer - Neural Graphics Performance at NVIDIA. Skills: Graphics performance engineering, CUDA, Slang, Optimization, Neural Graphics Performance. Implement, validate, release and maintain highly-optimized reconstruction and rendering algorithms using CUDA and Slang. Optimize data processing pipelines for low latency and maximum throughput”

What You'll Achieve.

Achieving full system utilization and occupancy; Enabling our latest hardware capabilities; Bridge the gap between the real world and simulations; Ensure outstanding performance

Industry & Context.

AI
Problems you'll solve

Performance challenges; Tradeoffs; Architectural alternatives

What They're Looking For.

Must Have

3 years of practical experience, fundamentals in real-time computer graphics, Expertise in GPU-accelerated software with CUDA, Slang, or other shading languages (GLSL, HLSL, Metal) for low-latency, high-throughput applications, Expertise defining and driving performance metrics through profiling and benchmarking, Proficiency with Python and C++, Track record releasing production-grade software, Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release), Excellent written, visual, and verbal communication to present performance challenges, tradeoffs, and architectural alternatives, Curiosity and drive to learn new technologies and partner across teams and functions

Nice to Have

Contributions to 3D game engines, graphics or computer vision SDKs, Algorithmic expertise in neural reconstruction (NERFs, Gaussian Splats), Experience developing high-performance distributed systems, Grounding in mathematical fundamentals such as linear algebra, numerical methods, statistics, and exploratory data analysis, History of multidisciplinary creativity and innovation around performance in multiple problem domains

What You'll Do.

release and maintain highly-optimized reconstruction and rendering algorithms using CUDA and Slang

Optimize data processing pipelines for low latency and maximum throughput

Influence software architecture

validation strategy and technical roadmaps to ensure outstanding performance

How You'll Work.

Team & Collaboration

Partner across teams and functions

Communication Scope

Excellent written, visual, and verbal communication; Present performance challenges, tradeoffs, and architectural alternatives

Full Job Description

NVIDIA is a world-leader in Gaussian Splatting and Neural reconstruction. Our team builds the Omniverse NuRec SDK to enable robotic, healthcare, and AV developers to build better models faster with closed-loop validation and closed-loop training grounded in real-world scenarios. Love GSplat? So do we! We are looking for a graphics performance engineer to push Gsplat and other accelerated libraries to speed of light, achieving full system utilization and occupancy and enabling our latest hardware capabilities. Your software will run on incredible amounts of data to bridge the gap between the real world and simulations. Join our amazing team and help us build the future of Physical AI! **What you 'll be doing:** * Implement, validate, release and maintain highly-optimized reconstruction and rendering algorithms using CUDA and Slang. * Optimize data processing pipelines for low latency and maximum throughput. * Influence software architecture, validation strategy and technical roadmaps to ensure outstanding performance. **What we need to see:** * Master's of Science in Computer Science or Electrical engineering (or equivalent experience). * 3 years of practical experience. * Strong fundamentals in real-time computer graphics. Expertise in GPU-accelerated software with CUDA, Slang, or other shading languages (GLSL, HLSL, Metal) for low-latency, high-throughput applications. * Expertise defining and driving performance metrics through profiling and benchmarking. * Proficiency with Python and C++. * Track record releasing production-grade software. Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release). * Excellent written, visual, and verbal communication to present performance challenges, tradeoffs, and architectural alternatives. * Curiosity and drive to learn new technologies and partner across teams and functions. **Ways to Stand Out from the Crowd:** * Contributions to 3D game engines, graphics o

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