Senior Research Engineer

We are looking for an outstanding Research Engineer to help turn brand-new research into working technology. You will work closely with research teams while staying deeply hands-on: prototyping new model and rendering ideas, making sharp design trade-offs, optimizing performance, integrating with downstream stacks, and building systems that can be evaluated, released, and improved over time.

What You'll Be Doing:

• Partner closely with research teams to shape neural graphics and world-simulation techniques while the field is still being invented
• Build prototypes and production-quality implementations across neural reconstruction, diffusion/world models, rendering, simulation, and real-time inference
• Connect generated worlds, reconstructed scenes, controllable simulation state, and downstream evaluation loops into coherent end-to-end systems
• Drive performance, latency, memory, temporal consistency, controllability, quality, and developer usability in real-time pipelines
• Make principled technical trade-offs across models, renderers, GPU systems, data pipelines, and product constraints
• Influence NVIDIA's broader neural graphics direction by grounding frontier ideas in systems that run, scale, and teach us what matters

What We Need to See:

• Background in Computer Science, Computer Graphics, Machine Learning, Electrical Engineering, or equivalent practical experience
• 8+ years of technical experience, or an equivalent record of exceptional technical contribution
• Deep hands-on expertise in one or more of: neural rendering, world models, diffusion/video generation, neural reconstruction, computer vision, simulation, or ML systems
• Strong implementation skill in real software systems, including debugging, optimization, integration, and performance-aware design
• Experience taking research concepts through the lifecycle from prototype to robust, evaluated, production-quality technology
• Ability to lead ambiguous, cross-team technical work and communicate the trade-offs behind architectural decisions

Ways to Stand Out from the crowd:

• Hands-on work with Gaussian Splatting, NeRFs, differentiable rendering, diffusion models, video generation, controllable world models, or neural content generation
• Experience building real-time graphics, simulation, robotics, AV, physical AI, game engine, or media creation systems
• Strong point of view on how AI will change entertainment, graphics, media, and interactive content creation
• Experience with CUDA, Slang, graphics APIs, real-time engines, GPU performance, or ML inference optimization
• Papers, patents, open-source leadership, shipped systems, or field-level technical impact in graphics, AI, simulation, or ML systems