As a Senior Deep Learning Performance Architect at NVIDIA, you will join the Deep Learning Architecture team to design and evaluate hardware architectures that enhance the performance, efficiency, and scalability of AI workloads. Your daily tasks include analyzing and optimizing large-scale deep learning models, particularly LLM inference and training in real-world settings, using Python and C++ for building performance and power models. You will identify system bottlenecks across compute, memory, and interconnect, evaluate PPA trade-offs, and collaborate with software, systems, and product teams to align hardware capabilities with workload requirements. Ideal candidates have a strong background in GPU/ASIC architecture, parallel computing, and deep learning workloads, along with experience in debugging, profiling, and performance tuning on real systems.
Skills
Python
C++
GPU
ASIC
Deep Learning
LLM
Batching
KV-cache
Latency/Tuning
Multi-node Scaling
Memory Hierarchy
Scalability
System Architecture
Performance Tuning
Profiling
Debugging
What you'll do
Design and evaluate hardware architectures to enhance AI workload performance, efficiency, and scalability.
Analyze and optimize large-scale deep learning workloads for real-world deployment.
Build and utilize performance models in Python/C++ to inform architecture decisions.
Identify and resolve system bottlenecks across compute, memory, and interconnect components.
Evaluate power-performance-area trade-offs to guide feature prioritization for new GPU designs.
What we're looking for
MS or PhD in Computer Science, Electrical Engineering, or equivalent experience.
5+ years of hands-on GPU/ASIC architecture and parallel computing experience.
Deep understanding of system architecture and performance optimization techniques.
Proficiency in Python and C++ for building performance models and analysis tools.
Experience optimizing large-scale deep learning workloads in production environments.
Market check
Salary context
This
$184,000–$287,500
range sits above
75%
of similar postings on FindRole.
Peer median band
$181,087–$262,400
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$185,162–$240,225
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
801 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 797 roles with salary data.
Remote (Us, Ca, Remote, US)11 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