Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
CUDA @ 4
Deep Learning @ 8
GPU @ 4
GenAI
Generative AI @ 4
LLM @ 4
Machine Learning @ 8
PyTorch @ 4
Python @ 6
SGLang @ 6
TensorRT @ 4
vLLM @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
At NVIDIA Lightspeed Studios, we are passionate about pushing the limits of technology. The team combines NVIDIA's AI and graphics technology with advanced games and tools to shape the future of gaming. This role focuses on bringing generative AI to games and taking new, unannounced projects powered by state-of-the-art AI models from research to real-time, interactive gaming experiences.
Existing projects include RTX Remix, Zorah, Project R2X, and NVIDIA AI for Gaming.
Responsibilities
- Build and ship software for upcoming, not-yet-announced projects that bring world models and video diffusion models to real-time gaming, from prototype to release.
- Train, fine-tune, and evaluate models, including data curation and adapting models to game-specific content and controls.
- Optimize models and inference for latency, token throughput, and quality using techniques such as distillation, quantization, and reduced-step sampling on RTX devices and in the cloud.
- Profile and remove bottlenecks across the stack, from model architecture to GPU kernels.
- Integrate models into Unreal Engine, Unity, and custom engines so they run efficiently alongside rendering.
- Lead technical decisions, mentor other engineers, and collaborate with NVIDIA Research, rendering, and art teams.
Requirements
- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- 12+ years of software engineering experience, including substantial hands-on experience shipping AI, deep learning, or machine learning systems.
- Expert-level C++ and Python.
- Hands-on experience training and fine-tuning deep learning models with PyTorch or a similar framework, including distributed training.
- Experience in one or more of the following areas: video generation, world models, diffusion or flow-matching models, transformers, or neural rendering.
- Experience optimizing GPU inference with CUDA, TensorRT, TensorRT-LLM, or Triton.
- A track record of turning complex prototypes into shipped products and communicating clearly across research, engineering, and art.
Preferred Qualifications
- Hands-on experience with interactive, action-conditioned, or real-time world models or video generation.
- Experience developing custom CUDA or Triton kernels.
- Experience with game engine development or real-time rendering pipelines.
- Open-source contributions such as Diffusers, FastVideo, vLLM, SGLang, or TensorRT-LLM; publications; or patents.
Benefits
- Equity and benefits are available.
- NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until October 2, 2026. This posting is for an existing vacancy.
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