Real job — pulled straight from NVIDIA’s careers page · Verified October 15, 2026 · No reposts.
Job description
NVIDIA is hiring a Deep Learning Performance Intern — a full-time, based in Shanghai, China role. Apply directly on NVIDIA's careers page below.
Deep Learning Performance Intern - 2027
Location: China, Shanghai
Time Type: Full time
Job Description
NVIDIA is developing GPU and system architectures that accelerate deep learning, automotive and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, perf optimization, projections, and analysis effort. In this position, you will have the chance to optimize deep learning processor 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 algorithms on different architectures
- Identify architecture and software performance bottlenecks and propose optimizations
- Explore new features and hardware capabilities on deep learning applications
What we need to see:
- BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)
- 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
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Frequently asked questions
What skills are required for Deep Learning Performance Intern at NVIDIA?
The required skills for Deep Learning Performance Intern at NVIDIA include: Deep Learning, Machine Learning.
What is the seniority level for Deep Learning Performance Intern at NVIDIA?
Deep Learning Performance Intern at NVIDIA is a Internship level position.
How do I apply for Deep Learning Performance Intern at NVIDIA?
You can view the full description and apply for Deep Learning Performance Intern at NVIDIA on EchoJobs: https://echojobs.io/job/nvidia-deep-learning-performance-intern-2027-3dg3m.