NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
Are you ready to build the future of data processing with NVIDIA? As a Senior Architect in Data Processing Systems for Analytics and Data Intelligence (ADI), you'll define and improve hardware and software architectures for diverse set of data processing workloads. Join us in our mission to deliver outstanding performance at scale, using our accelerated data processing platform that combines CPUs, GPUs, high-bandwidth networking, and more!
What you'll be doing:
- Co-design future architectures for NVIDIA's data processing platforms, targeting performance, efficiency, and cost.
- Engage deeply with end users, open-source communities, ISVs, storage partners, and CSPs to improve their experience by incorporating customer insights into roadmaps and reference architectures.
- Drive full-stack performance optimization, from CUDA kernels and accelerated libraries to system-level IO, shuffle, compression, and data movement.
- Collaborate with CPU, GPU, and platform architects to shape hardware features using workload analysis for hardware-software co-design.
- Partner with internal teams to build and apply constraint-based frameworks and optimization solvers to navigate complex design trade-offs across competing metrics.
- Develop benchmarking frameworks to evaluate performance sensitivities and guide hardware-software co-optimization
- Analyze production workloads throughout the data processing landscape to identify compute motifs, IO patterns, and optimization opportunities across the full platform stack.
What we need to see:
- MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
- 8+ years of experience in distributed data platforms, databases, systems engineering, performance architecture, accelerated computing, or HW/SW co-design.
- Extensive knowledge in one or more of these areas: data processing systems (databases, query engines, or vector search), accelerated computing, high-performance IO, CPU/GPU architecture, or large-scale performance analysis.
- Experience evaluating system-level trade-offs: compute, IO provisioning, memory subsystem development, network topology, and storage tiering across diverse workloads a strong plus.
- Ability to translate sophisticated system analysis into clear, actionable recommendations for silicon architects, software engineers, and executive leadership.
- Ability to work across matrixed organizations to drive alignment and deliver results.
Ways to stand out from the crowd:
- Hands-on experience with GPU-accelerated data processing (cuDF, RAPIDS, cuVS, CUDA).
- Deep familiarity with structured data engines and/or vector database systems.
- Experience with mathematical optimization solvers and understanding of optimization fundamentals.
- Background in network/storage architecture.
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 Engineering, Electrical Engineering, or a related field, or equivalent experience
- 8+ years of experience in distributed data platforms, databases, systems engineering, performance architecture, accelerated computing, or hardware/software co-design
- Extensive knowledge of data processing systems, accelerated computing, high-performance I/O, CPU/GPU architecture, or large-scale performance analysis
- Ability to translate sophisticated system analysis into clear, actionable recommendations for silicon architects, software engineers, and executive leadership
- Ability to work across matrixed organizations to drive alignment and deliver results
- Experience evaluating system-level trade-offs involving compute, I/O provisioning, memory subsystems, network topology, and storage tiering
- Hands-on experience with GPU-accelerated data processing, including cuDF, RAPIDS, cuVS, or CUDA
- Deep familiarity with structured data engines or vector database systems
- Experience with mathematical optimization solvers and understanding of optimization fundamentals
- Background in network or storage architecture
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.”
