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What you will be doing:
Develop and optimize diffusion-based generative models for high-fidelity, controllable image/video synthesis.
Design scalable architectures that reduce inference latency and enable real-time or interactive generation workflows.
Contribute to fundamental research and publish in top-tier conferences such as CVPR, NeurIPS, ICLR, ICCV, or SIGGRAPH.
Collaborate across teams to integrate research into simulation systems, digital avatars, robotics, and other NVIDIA platforms.
What we need to see:
PhD or equivalent experience in Computer Science, Computer Vision, Machine Learning, or a related field.
Strong foundation in generative models.
Experience with Python and PyTorch, and large-scale model training workflows.
Ability to conduct independent research and communicate findings clearly.
Passion for innovation in vision AI and a drive to see ideas move from research to impact.
Ways to stand out from the crowd:
Skills in efficient model architectures and efficient implementations.
Sharp mathematics skills.
You will also be eligible for equity and .
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