NVIDIA

DeepLearningComputerArchitect-NewCollegeGrad2026

$124–242k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Deep Learning Computer Architect - New College Grad 2026 at NVIDIA. Skills: Deep learning, Computer architecture, GPU computing. Contribute to GPU features. Advance AI state”

Industry & Context.

Problems you'll solve

Performance analysis

What They're Looking For.

Must Have

MS or PhD degree, 2+ years relevant experience, Computer architecture experience, Performance analysis experience, LLM workloads experience, Deep learning kernels experience, C++ programming fluency, GPU computing experience, Deep learning frameworks experience

Nice to Have

Python programming fluency

What You'll Do.

Contribute to GPU features

Keep up with DL research

Collaborate with diverse teams

Analyze DL methods behavior

Study feature benefits

How You'll Work.

Team & Collaboration

DL researchers; Hardware architects; Software engineers

Full Job Description

We are now looking for a Deep Learning Computer Architect! NVIDIA is seeking architects like you to help design hardware accelerator and processor architectures that enable state of the art machine learning and data analytics algorithms and applications on our next-generation mobile, embedded and datacenter platforms. This position offers you the opportunity to have a real impact in a dynamic, technology-focused company. **What you 'll be doing:** * As a member of our deep learning architecture team, you will contribute to features that help next-generation GPUs advance the state of AI. * This position requires you to keep up with the latest DL research and collaborate with diverse teams (internal and external to NVIDIA), including DL researchers, hardware architects, and software engineers. * Your day to day work will include analyzing the behavior of various deep learning methods, proposing new features to accelerate or enable various methods, and studying the benefits of the proposed features. **What we need to see:** * MS or PhD degree in computer science, computer architecture, electrical engineering or related field or equivalent experience. * 2+ years of relevant experience in at least a few of the following relevant areas is required in your work history: * Computer architecture, including GPU and system level architecture; * Performance analysis and optimization; * Experience with LLM workloads, including performance tuning considerations such as parallelization and fusion strategies;` * Experience with core deep learning kernels such as matrix multiply, attention, and communication convolution * Programming fluency with C++ and ideally Python * Experience with GPU computing (CUDA) * Experience with deep learning frameworks like PyTorch Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way

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