Deep Learning Performance Architect

NVIDIA is hiring a Deep Learning Performance Architect in Shanghai, China. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions Tensor Rt, C and Python among its tools and skills.
Level classes it as a senior role.
NVIDIA has 2,700+ other open roles on Level.

AI in this role

Develop highly optimized deep learning kernels and inference software for GPU-accelerated architectures.

tensor-rtcpythoncudaopencl

deep-learningperformance-optimizationkernel-developmentinference

We are now looking for a Deep Learning Performance Software Engineer! We are expanding our research and development for Inference. We seek excellent Software Engineers and Senior Software Engineers to join our team.

We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions. Collaborate with the deep learning community to implement the latest algorithms for public release in Tensor-RT. Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary.

What you’ll be doing:

Develop highly optimized deep learning kernels for inference
Do performance optimization, analysis, and tuning
Work with cross-collaborative teams across automotive, image understanding, and speech understanding to develop innovative solutions
Occasionally travel to conferences and customers for technical consultation and training

What we need to see:

Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)
SW Agile skills helpful
Excellent C/C++ programming and software design skills
Python experience a plus
Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU
GPU programming experience (CUDA or OpenCL) desired
5 years of relevant work experience

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!

How we rate this

Deep Learning Performance Architect at NVIDIA rates 90 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

Deep Learning Performance Architect 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 August 27, 2026.
Seniority: senior.
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

Deep learningPerformance OptimizationKernel DevelopmentInferenceTensor RtCPythonCUDA

Questions you could be asked

Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where performance optimization was part of your work. What did you do?
Tell me about a project where kernel development was part of your work. What did you do?
Tell me about a project where inference was part of your work. What did you do?
Walk me through how you've used Tensor Rt in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Deep learning, Performance Optimization, Kernel Development, Inference, and Tensor Rt. 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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