below marketmost similar roles pay hereabove market
This role pays more than
85%
of similar roles. Most pay
$155,000–$235,750
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$195k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
As a Senior Architect - Data Processing Systems, Analytics and Data Intelligence, you will join the team to define and improve hardware and software architectures for diverse data processing workloads. You will co-design future architectures for data processing platforms, focusing on performance, efficiency, and cost. Your daily responsibilities include driving full-stack performance optimization, developing benchmarking frameworks, and analyzing production workloads to identify compute motifs and IO patterns. You will collaborate with CPU, GPU, and platform architects to shape hardware features using workload analysis. Required skills include expertise in distributed data platforms, databases, query engines, vector search, and accelerated computing. You will utilize technologies such as CUDA, cuDF, RAPIDS, and cuVS while navigating complex design trade-offs across memory subsystems, network topology, and storage tiering for high-performance data processing.
What does a Architect earn?
Median $225000 from 45 postings across 26 companies.
Co-design future hardware and software architectures for NVIDIA's data processing platforms.
Incorporate customer insights from end users and partners into product roadmaps and reference architectures.
Drive full-stack performance optimization across CUDA kernels, accelerated libraries, and system-level IO.
Shape hardware features by performing workload analysis for hardware-software co-design.
Build and apply constraint-based frameworks and optimization solvers to navigate complex design trade-offs.
Develop benchmarking frameworks to evaluate performance sensitivities and guide co-optimization.
Analyze production workloads to identify compute motifs, IO patterns, and optimization opportunities.
What we're looking for
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 data processing systems, 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.
Experience evaluating system-level trade-offs including compute, IO provisioning, memory subsystem development, network topology, and storage tiering (preferred).
Hands-on experience with GPU-accelerated data processing such as cuDF, RAPIDS, cuVS, or CUDA (preferred).
Deep familiarity with structured data engines, vector database systems, or mathematical optimization solvers (preferred).