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Senior Architect - Data Processing Systems, Analytics and Data Intelligence

NVIDIA· Architect
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Hybrid (Remote / Local)$184k - $287.5kFull-timePosted 3d ago

About the role

Senior Architect in Data Processing Systems for Analytics and Data Intelligence (ADI) at NVIDIA, shaping hardware and software architectures for diverse data processing workloads and delivering high-performance, scalable accelerated data processing platform combining CPUs, GPUs, and high-bandwidth networking.

Responsibilities

  • Co-design future architectures for NVIDIA's data processing platforms, targeting performance, efficiency, and cost.
  • Engage with end users, open-source communities, ISVs, storage partners, and CSPs to incorporate 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 design trade-offs across metrics.
  • Develop benchmarking frameworks to evaluate performance sensitivities and guide hardware-software co-optimization.
  • Analyze production workloads to identify compute motifs, IO patterns, and optimization opportunities across the platform stack.

Qualifications

  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or 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 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 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.

Skills

Required:Data processing systemsAccelerated computingPerformance analysis
Nice to have:Optimization

Benefits

  • equity
  • benefits described by NVIDIA benefits page
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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