Senior Deep Learning Systems Architect

at Nvidia

📍 Santa Clara, United States

USD 224,000-356,500 per year

SENIOR

✅ On-site

Used Tools & Technologies

Not specified

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Python @ 6 Algorithms @ 4 Machine Learning @ 4 TensorFlow @ 7 PyTorch @ 7 CUDA @ 1 GPU @ 1 Deep Learning @ 4 AI @ 4 OpenCL @ 1 HPC @ 1 Performance Analysis @ 4 JAX @ 7

Details

We are looking for a Senior Deep Learning Systems Architect to help design hardware accelerator and processor architectures that enable state-of-the-art machine learning and data analytics algorithms and applications on next-generation mobile, embedded and datacenter platforms at NVIDIA.

Responsibilities

Contribute to features that advance next-generation GPUs and AI systems.
Keep up with the latest deep learning research and collaborate with diverse teams, including DL researchers, hardware architects, and software engineers.
Participate in engineering projects and co-design system architectures from conception, specification, and prototyping.
Understand various AI/DL workloads and their mapping to underlying hardware and systems; identify improvements and bottlenecks and propose solutions.
Perform comprehensive analyses from first principles of deep learning techniques and system optimizations; build analytical models, implement prototypes, and run benchmarking to validate ideas.

Requirements

MS (or equivalent experience) or PhD in computer science, computer architecture, electrical engineering, or related field with 10+ years of relevant work experience. Equivalent experience in relevant areas may substitute for an advanced degree.
Strong background in several of the following areas: machine learning (focus on deep neural networks), solid understanding of DL fundamentals, adapting and training DNNs, and developing code for DNN training frameworks such as PyTorch, TensorFlow, or JAX.
Experience in numerical analysis, performance analysis and optimization, and computer architecture.
Programming fluency in C++ and ideally Python.
Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a strong plus.

Compensation and Benefits

Base salary range: 224,000 USD - 356,500 USD (final base salary determined based on location, experience, and internal pay).
Eligible for equity and benefits (see NVIDIA benefits link in original posting).

Company & Application Details

Employer: NVIDIA. This posting is for an existing vacancy.
Applications for this job will be accepted at least until July 19, 2026.
NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.