Senior Architect – Data Processing Systems, Analytics, Data Intelligence

NVIDIA

. Co-design future architectures for NVIDIA's data processing platforms .

Posted 10/16/2026full-timeRemote • United StatesSenior💰 $184,000 - $356,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data processing architectures, performance optimization, and hardware-software co-design, with a strong focus on GPU-accelerated computing and system-level analysis. Capable of translating complex system evaluations into actionable insights while collaborating effectively across diverse teams.

Highest-signal resume keywords

Data Processing SystemsAccelerated ComputingPerformance ArchitectureGPU-Accelerated Data ProcessingMathematical Optimization Solvers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

CUDA KernelsPerformance OptimizationBenchmarking FrameworksSystem-Level IOData MovementCompute Motifs AnalysisIO Patterns AnalysisConstraint-Based FrameworksOptimization SolversLarge-Scale Performance Analysis

Soft Skills

Clear CommunicationCollaboration Across Matrixed Organizations

Certifications & Qualifications

MS or PhD in Computer ScienceComputer EngineeringElectrical Engineering

Industry Keywords

Distributed Data PlatformsDatabasesSystems EngineeringHW/SW Co-DesignNetwork ArchitectureStorage ArchitectureMemory Subsystem DevelopmentNetwork TopologyStorage TieringStructured Data Engines

About the role

Key responsibilities & impact

Co-design future architectures for NVIDIA's data processing platforms
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 on hardware-software co-design
Build and apply constraint-based frameworks and optimization solvers to navigate design trade-offs
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

Requirements

What you’ll need

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: data processing systems, accelerated computing, high-performance IO, CPU/GPU architecture, or large-scale performance analysis
Experience evaluating system-level trade-offs across compute, IO provisioning, memory subsystem development, network topology, and storage tiering is a strong plus
Ability to translate sophisticated system analysis into clear, actionable recommendations
Ability to work across matrixed organizations
Hands-on experience with GPU-accelerated data processing is a plus
Deep familiarity with structured data engines and/or vector database systems is a plus
Experience with mathematical optimization solvers and optimization fundamentals is a plus
Background in network/storage architecture is a plus

Benefits

Comp & perks

Equity
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