Senior Hardware Architect, Deep Learning GPU and System

NVIDIA is hiring a Senior Hardware Architect, Deep Learning GPU and System. 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 GPU, Deep learning and hardware architecture.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Design and analyze next-generation GPU hardware architectures and systems to accelerate deep learning and AI workloads.

GPUDeep learning

hardware-architecturedeep-learninggpu-computingperformance-analysis

At NVIDIA, we push the boundaries of Artificial Intelligence using Deep Learning every day, designing better algorithms, hardware and software. By joining the Compute Deep Learning Architecture team you would be in an outstanding position to influence all three and help us push the boundaries even farther in large number of fields like datacenters and autonomous machines. We are looking for remarkable candidate passionate about AI and Deep Learning as much as we are. Would you like to make a difference?

What you'll be doing:

As a member of our Hardware architecture deep learning team, you will contribute to features that help next-generation GPUs and systems advance the state of AI.
This position requires you to collaborate with other hardware and software engineers as well as DL researchers.
Your day to day work will include analyzing the behavior of various deep learning methods on current and future hardware architectures and propose new features to accelerate it. The features could be HW, SW or Algorithmic - usually combining all.
The main focus of this job is from hardware architecture perspective and workload performance.

What we need to see:

A degree or equivalent experience in computer science, electrical engineering or related field.
8+ years of experience in at least some of the following relevant areas is required: Performance, Hardware Architecture, Deep Learning analysis.
A familiarity with GPU computing (Nvidia or others) is a plus.
Excellent interpersonal skills, people who like to collaborate and work within a team.
innovation, motivation and passion.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. An AI-powered robot can communicate and learn motor skills through trial and error. This is truly an outstanding time. The era of AI has begun. Come and join us!

How we rate this

Senior Hardware Architect, Deep Learning GPU and System 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

Senior Hardware Architect, Deep Learning GPU and System is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Israel, Yokneam.
The job was posted on April 28, 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

Hardware ArchitectureDeep learningGPU ComputingPerformance AnalysisGPU

Questions you could be asked

Tell me about a project where hardware architecture was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where gpu computing was part of your work. What did you do?
Tell me about a project where performance analysis was part of your work. What did you do?
Walk me through how you've used GPU in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Hardware Architecture, Deep learning, GPU Computing, Performance Analysis, and GPU. 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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