
NVIDIA
Deep Learning Engineer, Generative AI and 3D Reconstruction
Full-time
On-site, Tokyo, Japan
13 days ago
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About
What you will be doing:
- Implement and improve deep learning models to generate high-fidelity 3D representations from 2D images using the latest advances in neural rendering, Neural Radiance Fields (NeRF), Gaussian Splatting and photogrammetry.
- Design workarounds to eliminate artifacts that result from real-world adversarial effects, such as non-stationary scenes and lens irregularities.
- Optimize algorithms for efficient training and deployment of these models for the reproduction of very large scale real-life environments.
- Help customers to build digital twin solutions that combine the strengths of neural- and classic- rendering technologies for the generation of training and test data for computer vision foundation models.
What we need to see:
- University degree, or equivalent knowledge, in Computer Science, Computer Engineering, Electrical Engineering or Physics/Mathematics degree with Computer Science experience.
- Proficiency in C++, Python, data structures and algorithms and a solid understanding of computer architecture and operating systems.
- 3+ years experience developing algorithms in more than one of the following areas: virtual / augmented reality, photogrammetry, 3D reconstruction, NeRF / 3DGS / neural rendering, visual generative AI, foundation models, vision language models, style transfer.
- Strong understanding of traditional graphics rendering pipeline, such as rasterization and ray-tracing, OpenGL/Vulkan and shading languages.
- Knowledge of gaming engines, such as UE/Unity.
Ways to stand out from the crowd:
- Experience with multi-modal generative AI.
- Experience handling very large datasets and using large-scale cloud infra for training and deploying AI models.
- Contribution to open-source projects (can be your private project). Please provide link to github repository.
- Extensive experience in contributing to the field of visual generative models, with a strong publication record in top conferences or journals (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH, etc.)
- Achievements in programming or machine learning competitions, such as Kaggle, HackerRank, TopCoder, etc.
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