About the role
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 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.
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.Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
