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.
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 the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.You will also be eligible for equity and benefits.
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.Skills Required
- MS or PhD in computer science, computer architecture, electrical engineering or related field with 10+ years relevant experience (or equivalent experience)
- Strong background in Machine Learning with focus on Deep Neural Networks and DL fundamentals; experience adapting and training DNNs
- Experience 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 with C++
- Programming experience with Python
- Work experience with GPU computing (CUDA, OpenCL, OpenACC)
- Experience with high-performance computing (MPI, OpenMP)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
