Senior Architect - Data Processing Systems, Analytics and Data Intelligence
About The Position
NVIDIA is hiring a Senior Architect in Data Processing Systems for Analytics and Data Intelligence (ADI) to define and improve hardware and software architectures for diverse data-processing workloads. The role focuses on building NVIDIA’s accelerated data-processing platform, which combines CPUs, GPUs, high-bandwidth networking, and other technologies, to deliver performance, efficiency, and cost effectiveness at scale. The architect will co-design future platform architectures, incorporate input from end users and ecosystem partners into roadmaps and reference architectures, and drive full-stack performance optimization. The position also works with CPU, GPU, and platform architects on hardware-software co-design; develops constraint-based frameworks and optimization solvers to navigate design trade-offs; creates benchmarking frameworks; and analyzes production workloads to identify compute motifs, IO patterns, and optimization opportunities.
Requirements
- 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 in one or more of the following areas: data-processing systems (databases, query engines, or vector search), accelerated computing, high-performance IO, 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.
Nice To Haves
- Experience evaluating system-level trade-offs, including compute, IO provisioning, memory subsystem development, network topology, and storage tiering across diverse workloads.
- Hands-on experience with GPU-accelerated data processing, such as cuDF, RAPIDS, cuVS, or 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 or storage architecture.
Responsibilities
- Co-design future architectures for NVIDIA data-processing platforms, targeting performance, efficiency, and cost.
- Engage with end users, open-source communities, ISVs, storage partners, and CSPs, 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 for complex design trade-offs.
- 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, IO patterns, and optimization opportunities across the platform stack.
Benefits
- Eligible for equity and benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
