Research Scientist, Generative AI for Graphics and Gaming

Benefits

• Stay current on AI and graphics research and work with product, driver, hardware, engine, and platform teams to turn promising ideas into shipping, user-visible features.
• What we need to see: MS or PhD in Computer Science/Engineering, Electrical Engineering, Applied Mathematics, or a related field (or equivalent experience). 3+ years of deep learning experience in image/video generation, graphics, computer vision, or related fields, with a solid understanding of core DL fundamentals.
• Extensive hands-on experience training large models on multi-GPU clusters (hundreds to thousands of GPUs), building robust distributed training pipelines and debugging at scale, with strong proficiency in PyTorch required; familiarity with GPU architecture, CUDA abstractions, and efficiency techniques (e.g., distillation, pruning, low-precision training/inference) is a plus.
• Background in graphics—such as rendering pipelines or game engines—and experience with generative models, neural rendering, or reconstruction is a plus.
• Proven track record of impactful research and shipped ideas (e.g., leading publications, production features, or widely used tools), and strong communication and collaboration skills in cross-functional teams.
• NVIDIA’s invention of the GPU 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, we are increasingly known as “the AI computing company”.
• Do you love the challenge of pushing what's possible in realtime interactive graphics and Generative AI? If so, we want to hear from you!