Software Engineering Intern, Neural Reconstruction and Rendering - 2027

NVIDIA is hiring a Software Engineering Intern, Neural Reconstruction and Rendering - 2027 in Shanghai, China. Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch and computer vision.
Level classifies it as an internship.
Level lists 2,600+ other open roles at NVIDIA.
The role was posted in the last few days.

AI in this role

PyTorch

computer-vision

Join NVIDIA’s Real2Sim team to turn real-world captures into accurate, editable simulation environments for robotics. You will develop and evaluate reconstruction and rendering methods that improve scene geometry, visual fidelity, and computational efficiency, contributing to workflows built around NVIDIA NuRec and Isaac Sim.

What you’ll be doing

Improve neural scene reconstruction through Gaussian optimization, sampling, and geometry-aware learning, addressing incomplete surfaces, artifacts, and challenging viewpoints.
Explore surface extraction, material estimation, relighting, and generative refinement to make reconstructed environments more accurate and editable.
Implement and optimize research methods in reusable reconstruction and rendering pipelines, collaborating with engineers to integrate results into NuRec and Isaac Sim workflows.
Build reproducible experiments that measure geometric accuracy, novel-view quality, consistency across views and time, runtime, and GPU memory, and evaluate the impact on a selected robotics simulation use case.

What we need to see

Pursuing a master’s or doctoral degree in computer science, computer graphics, computer vision, robotics, or a related field.
Strong Python and PyTorch skills, with experience implementing, training, and debugging research models on GPUs.
Hands-on research or project experience in 3D Gaussian Splatting, neural rendering, multi-view reconstruction, or closely related methods.
Solid foundations in 3D geometry, camera models, numerical optimization, and machine learning.
Ability to reproduce research results, design controlled comparisons, analyze failure cases, and collaborate effectively with researchers and engineers.

Ways to stand out from the crowd

Depth in Gaussian sampling and densification, including MCMC-based optimization; surface reconstruction and meshing; or inverse rendering and relighting.
Experience with generative priors for reconstruction, scene completion, or rendering, including preserving geometry and consistency across views.
Experience with C++, CUDA, Slang, differentiable rendering, or GPU performance profiling.
Familiarity with gsplat, 3DGUT/3DGRT, NuRec, OpenUSD, or Isaac Sim; effective use of AI-assisted development with code review and validation.

How we rate this

Software Engineering Intern, Neural Reconstruction and Rendering - 2027 at NVIDIA rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Software Engineering Intern, Neural Reconstruction and Rendering - 2027 is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in China, Shanghai.
The job was posted on November 13, 2026.
Seniority: intern.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionPyTorch

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Walk me through how you've used PyTorch in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer vision and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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