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.
Do you obsess about software engineering? So do we! We are looking for a strong System Engineer to develop and maintain NVIDIA's software ecosystem for neural graphics, including key OSS platforms like GSplat. Your software will serve a booming community of developers eager 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 SDKs, APIs, libraries for Neural Reconstruction, including key Open Source projects like GSplat.
Influence software architecture, validation strategy and technical roadmaps to ensure outstanding usability for our developers across many fields, from research to large-scale production use.
What we need to see:
Master's of Science in Computer Science or Electrical engineering or equivalent experience.
5+ years of practical experience.
Track record developing and maintaining developer-focused, production-grade software for computer graphics or computer vision (for instance game engines, rendering software).
Proficiency with Python and C++.
Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release).
Experience developing high-performance distributed systems (micro-services, Kubernetes).
Excellent written, visual, and verbal communication to present architectural challenges, tradeoffs, and alternatives.
Curiosity and drive to learn new technologies and partner across teams and functions.
Ways to Stand Out from the Crowd:
Strong fundamentals in real-time graphics or other performance-critical domains.
Experience in GPU-accelerated software with CUDA, Slang, or other shading languages (GLSL, HLSL, Metal) for low-latency, high-throughput applications.
Algorithmic expertise in neural reconstruction (NERFs, Gaussian Splats).
History of multidisciplinary creativity and innovation around software engineering in multiple problem domains.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
