Senior Deep Learning Systems Architect

NVIDIA is hiring a Senior Deep Learning Systems Architect in Santa Clara, United States. It pays $224k-$357k a year and 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.
The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
Level classes it as a senior role.
NVIDIA has 2,600+ other open roles on Level.

AI in this role

pytorchtensorflowjax

We are now looking for a Senior Deep Learning Systems 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 and systems advancing 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.
As a system architect for NVIDIA’s offerings for AI systems, you will participate in engineering projects and co-design architecture for systems from conception, specification and prototyping.
Understanding various AI/DL workloads and their mapping to underlying HW and Systems. Identifying potential improvements and bottlenecks, proposing solutions to address existing gaps, and accelerate/improve current systems/methods.
Comprehensive analyses from first principles of various deep learning techniques, system optimizations to build out analytical models as well as implementing prototypes, and benchmarking to test/prove ideas.

What we need to see:

MS (or equivalent experience) or PhD degree in computer science, computer architecture, electrical engineering or related field with 10+ years of relevant work experience. Additional equivalent experience in several of the relevant areas listed below can substitute for an advanced degree.
Strong background in at least a few of the following relevant areas is required in your work history: Machine learning (with focus on Deep Neural Networks), including a solid understanding of DL fundamentals; Experience adapting and training DNNs for various tasks; Experience developing code for one or more of the DNN training frameworks (such as PyTorch, TensorFlow or JAX): Numerical analysis, Performance analysis and optimization & Computer architecture.
Programming fluency with C++ and ideally Python.
Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a huge plus.

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. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you! Come, join our Deep Learning Architecture team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 224,000 USD – 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Senior Deep Learning Systems Architect at NVIDIA rates 96 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 Deep Learning Systems Architect is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $224k-$357k a year.
The role is based in US, CA, Santa Clara.
The job was posted on July 15, 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

PyTorchTensorFlowJAX

Questions you could be asked

What's a project where you used PyTorch hands-on?
Walk me through how you've used TensorFlow in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: PyTorch, TensorFlow, and JAX. 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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