NVIDIA is seeking a Senior Kernel Performance Architect to join its Deep Learning Architecture team, where you will develop cutting-edge GPU-accelerated system architectures that enhance machine learning and data analytics performance. Your daily tasks include prototyping high-performance software, analyzing and optimizing software performance using various tools, and collaborating with cross-functional teams such as CUDA Compiler, AI/ML training, inference performance, and hardware architecture groups to identify and resolve critical deep learning bottlenecks. Ideal candidates possess a Master’s or PhD in Computer Science, Electrical Engineering, or related fields, along with extensive experience in high-performance kernel development, GPU computing, and parallel programming models. Proficiency in Python, C, and C++ is essential, as well as expertise in analytical performance modeling and profiling techniques. This role offers the opportunity to contribute significantly to NVIDIA’s mission of advancing real-time, cost-effective AI computing solutions at scale.
Skills
Python
C
C++
GPU
CUDA
Parallel Programming
Performance Modeling
Profiling
Kernel Development
Math Library Optimization
Deep Learning
Machine Learning
What you'll do
Craft GPU-accelerated system architectures to enhance deep learning performance.
Prototype high-performance software for deep learning and data analytics workloads.
Analyze and optimize software performance using models, simulators, and test suites.
Identify and resolve critical performance issues with CUDA Compiler teams.
Optimize deep learning layers in collaboration with AI/ML training and inference teams.
Define expectations for emerging deep learning hardware features with hardware architecture teams.
What we're looking for
Master's or PhD in Computer Science, Electrical Engineering, or equivalent experience.
5+ years of industry or research experience in relevant fields.
Strong foundation in machine learning and deep learning fundamentals.
Experience with high-performance kernel work and math library performance analysis.
Fluency in Python, C, and C++ programming languages.
Familiarity with GPU computing and parallel programming models.
Hands-on experience with analytical performance modeling and profiling.
Market check
Salary context
This
$152,000–$218,500
range sits above
23%
of similar postings on FindRole.
Peer median band
$170,300–$262,800
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$196,750–$235,750
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
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
802 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 798 roles with salary data.
Remote (Us, Ca, Remote, US)10 days ago
$152,000–$241,500
Python
C
C++
CUDA
MPI
OpenMP
HPC
GPU
Deep Learning
Machine Learning
Performance Modeling
Systems Performance Analysis
AI Inference Workloads
CUDA Kernels
Custom ASIC Hardware