Senior Architect - Data Processing Systems, Analytics and Data Intelligence

at Nvidia

📍 Santa Clara, United States

USD 184,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
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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.

CUDA @ 4 GPU @ 4 Leadership @ 6 Networking Performance Analysis @ 4 Performance Optimization

Details

NVIDIA is building the future of data processing with an accelerated data processing platform that combines CPUs, GPUs, high-bandwidth networking, and other technologies. The Analytics and Data Intelligence team is seeking a Senior Architect to define and improve hardware and software architectures for diverse data processing workloads, delivering performance at scale.

Responsibilities

Co-design future architectures for NVIDIA's data processing platforms, targeting performance, efficiency, and cost.
Engage with end users, open-source communities, independent software vendors, storage partners, and cloud service providers to incorporate customer insights into roadmaps and reference architectures.
Drive full-stack performance optimization, from CUDA kernels and accelerated libraries to system-level I/O, shuffle, compression, and data movement.
Collaborate with CPU, GPU, and platform architects to shape hardware features through workload analysis and hardware-software co-design.
Partner with internal teams to build and apply constraint-based frameworks and optimization solvers for complex design trade-offs across competing metrics.
Develop benchmarking frameworks to evaluate performance sensitivities and guide hardware-software co-optimization.
Analyze production workloads across the data processing landscape to identify compute motifs, I/O patterns, and optimization opportunities throughout the platform stack.

Requirements

Master's degree 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 in one or more of the following areas: data processing systems, databases, query engines, vector search, accelerated computing, high-performance I/O, CPU/GPU architecture, or large-scale performance analysis.
Experience evaluating system-level trade-offs involving compute, I/O provisioning, memory subsystem development, network topology, and storage tiering across diverse workloads is 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.

Preferred Qualifications

Hands-on experience with GPU-accelerated data processing, including cuDF, RAPIDS, cuVS, or CUDA.
Deep familiarity with structured data engines and/or vector database systems.
Experience with mathematical optimization solvers and an understanding of optimization fundamentals.
Background in network and storage architecture.

Compensation and Benefits

The base salary range is USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. Compensation is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until October 20, 2026. NVIDIA is an equal opportunity employer.