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

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
The posting mentions GPU, deep learning and computer architecture 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

Analyze and optimize deep learning workload performance across different hardware and software architectures.

gpu

deep-learningcomputer-architectureperformance-optimizationhpcmachine-learning

NVIDIA is developing GPU and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to analyze deep learning performance on different hardware and software architecture and make a significant impact in a dynamic technology focused company

What you’ll be doing:

Analyze performance of various deep learning workloads on different architectures
Identify architecture and software performance bottlenecks
Explore new features and system configurations to achieve better performance and energy efficiency

What we need to see:

BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)
3+ years of working experience in relevant directions (e.g., hardware system, datacenter hardware, LLM workloads on data center) will be a plus
Be familiar with GPU or accelerator-based deep learning platform and software stack
A strong background in computer architecture
Experience on system architecture design and performance optimization
Familiar with machine learning and deep learning frameworks

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 July 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 learningComputer ArchitecturePerformance OptimizationHpcMachine learningGPU

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 computer architecture 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 hpc was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Deep learning, Computer Architecture, Performance Optimization, Hpc, and Machine learning. 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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