Research Scientist, AI for Graphics and Gaming - New College Grad 2026
at Nvidia
USD 168,000-264,500 per year
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Communication @ 6
Mathematics @ 3
Debugging @ 6
Experimentation @ 3
LLM @ 6
PyTorch @ 6
CUDA @ 2
GPU @ 3
- 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
We are seeking a Research Scientist in Generative AI for Graphics and Gaming to join NVIDIA's Applied Deep Learning Research team. You will work on deep learning research that advances real-time graphics and interactive game experiences — from neural rendering and real-time image/video generation to world models, AI-driven characters, and LLM-powered gameplay. The role involves conducting cutting-edge research, training large models at scale, prototyping in real-time engines, and collaborating with product, driver, and hardware teams to bring research into shipping products. You will have access to abundant GPU compute for experimentation and large-scale training.
Responsibilities
- Research and develop AI models that improve real-time graphics quality, robustness, performance, and latency, and enable new interactive experiences (world models, LLM-driven gameplay, AI-driven characters).
- Design and run large-scale pre-training and post-training for foundation models for graphics and gaming using NVIDIA’s GPU infrastructure.
- Build and own data pipelines and datasets for foundation models and large-scale training, spanning synthetic data, in-engine captures, and real-world content.
- Develop and prototype models for real-time image, video, and 3D content generation in modern game engines and graphics frameworks and create demos that showcase player-visible benefits.
- Stay current on AI and graphics research and collaborate with product, driver, hardware, engine, and platform teams to turn promising ideas into shipping features.
Requirements
- Pursuing a PhD in Computer Science/Engineering, Electrical Engineering, Applied Mathematics, or a related field (or equivalent experience).
- Deep learning experience in image/video generation, graphics, computer vision, or related fields, with solid understanding of core DL fundamentals.
- Hands-on experience training large models on multi-GPU clusters (hundreds to thousands of GPUs), building robust distributed training pipelines and debugging at scale; strong proficiency in PyTorch is 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 (publications, production features, or widely used tools), plus strong communication and collaboration skills in cross-functional teams.
Benefits & Additional Information
- Base salary range: 168,000 USD - 264,500 USD (final base salary determined by location, experience, and internal pay equity).
- Eligible for equity and benefits (see NVIDIA benefits pages).
- Applications accepted at least until January 31, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.