NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology, and extraordinary people, NVIDIA is looking for a strong technical senior architect to join us in shaping the future. Senior Architects are innovators who can translate business needs into workable technology solutions. Their expertise is deep and broad. They are hands on, producing both detailed technical work and high-level architectural designs.
As a Senior architect in the AI Networking Research team, you will explore technological challenges on accelerate networking and building AI data centers. Research new transport functions and semantics for optimizing AI workloads, AI systems communication and accelerations and much more. You will also be leading architectural and development efforts across numerous technological fields, related to the modern AI data center, such as distributed AI and deep learning solutions, data analytics, High Performance Computing (HPC), Software Defined Networking (SDN), virtualization, storage, and more.
What you’ll be doing:
Enhance NVIDIA's GPU Networking offerings for accelerating AI workloads, such as NVIDIA Dynamo, NVIDIA NIXL and NVIDIA UCX, tailored to the unique requirements of AI workloads.
Co-design hardware features (e.g., in GPUs, DPUs, or interconnects) that accelerate data movement and enable new capabilities for inference and model serving.
Identify and evaluate new technologies, innovations and partner relationships for alignment with our technology roadmap and business value.
Lead architecture and design of new technologies and innovations such as runtime systems, communication libraries, AI-specific technologies.
Lead proof-of-concept development to evaluate and drive such technologies.
What we need to see:
Hold a M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).
5+ years of industry experience (or equivalent) in system architecture, AI systems architecture, scaling of AI, Parallelism of AI frameworks, or deep learning training workloads.
Experienced in algorithm design, system programming, computer architecture and operating systems.
Experienced in virtualization, networking and storage.
Deep understanding of performance profiling and optimization techniques, together with defining and using hardware features.
Strong programming and software development skills.
Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Ways to stand out from the crowd:
Shown research track record.
Have experience and passion for system architecture, CPU/GPU/memory/storage/networking.
Stellar communication skills.
Knowledge in Deep Learning frameworks and AI communication libraries (NCCL, UCX, MPI and equivalents).
Deep understanding of Inference and Training workloads and optimizations, like Prefill/Decode, data parallelism, Tensor parallelism, FDSP and others.
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 and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse 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
- M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience
- 5+ years of industry experience in system architecture, AI systems architecture, AI scaling, AI framework parallelism, or deep learning training workloads
- Experience with algorithm design, system programming, computer architecture, and operating systems
- Experience with virtualization, networking, and storage
- Deep understanding of performance profiling and optimization techniques, including defining and using hardware features
- Strong programming and software development skills
- Ability to communicate effectively in a multinational, multi-time-zone corporate environment
- Research track record
- Experience with CPU, GPU, memory, storage, and networking system architecture
- Strong communication skills
- Knowledge of deep learning frameworks and AI communication libraries such as NCCL, UCX, and MPI
- Understanding of inference and training workloads and optimizations, including Prefill/Decode, data parallelism, tensor parallelism, and FDSP
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.”
