Senior Research Engineer, Interactive World Models

Details

FlashDreams and FastGen are NVIDIA’s core technologies for turning video models into real-time world simulations. The stack spans model adaptation for faster generation and richer control, plus the execution layer that runs those models as responsive experiences. The work supports generative worlds for autonomous-driving simulation, robot policy development and testing, game worlds, medical simulation, and virtual training.

As a Senior Research Engineer, you will lead engineering across model development and runtime systems, building capabilities and turning research into systems that work in real applications. You will work across the world-model ecosystem, collaborating with leading researchers and helping shape a new computing platform for real-world AI applications.

Responsibilities

• Build and optimize the continuous autoregressive serving loop, including per-step control inputs, model and KV-cache state management, GPU inference, frame streaming, and model integrations.
• Advance production-ready world models by working with researchers on few-step distillation, causal or autoregressive generation, reward fine-tuning, action conditioning, and long-horizon spatiotemporal memory and consistency.
• Lead end-to-end delivery of capabilities such as multi-user experiences and simulation workflows, from prototype through evaluation, integration, and release.
• Partner with applied researchers and domain teams to meet quality, performance, and reliability goals.

Requirements

• Experience in one or more areas such as video or world models, diffusion and generative modeling, model distillation and adaptation, simulation, robotics, computer vision, or real-time, stateful machine-learning systems.
• MS or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
• 5+ years of equivalent experience in applied machine learning or research engineering.
• A record of advancing applied ML or ML systems through research, open-source software, patents, or deployed technology, including taking ambiguous ideas through thorough evaluation and release.
• Hands-on experience with Python, PyTorch, and GPU-accelerated training, inference, performance optimization, or serving.
• Strong research and engineering judgment, with the ability to find practical solutions to open-ended problems and deliver reliable results within software and hardware constraints.

Preferred Qualifications

• Experience with post-training generative video models, including distillation, self-forcing, action conditioning, or long-horizon memory.
• Experience building and optimizing real-time, stateful generative inference systems, including history and KV-cache management, GPU kernels, quantization, parallel execution, streaming, scheduling, or multi-user serving.
• Technical stewardship of an open-source ML project used by researchers or developers, with work spanning architecture, APIs, model ecosystems, releases, maintainer practices, documentation, benchmarks, adoption, or community.
• Relevant ecosystems include vLLM, SGLang, FastVideo, LightX2V, Diffusers, FlashInfer, and comparable platforms.

Compensation and Benefits

• Base salary range: $184,000–$287,500 for Level 4.
• Base salary range: $224,000–$356,500 for Level 5.
• Base salary is determined based on location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• This is a full-time position.

Applications will be accepted at least until August 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.