As a Senior High Performance Computing (HPC) and AI Networking Performance Research and Analysis Engineer at NVIDIA, you will join the Performance group to profile and analyze AI workloads on large-scale GPU and CPU clusters for distributed deep learning LLM training, focusing on collectives communication and networking. Your day-to-day responsibilities include benchmarking, profiling, and analyzing performance bottlenecks across various hardware platforms like HCAs, switches, CPUs, GPUs, and systems, while developing performance analysis tools to optimize network communications using NVIDIA Collective Communications Library (NCCL). You will collaborate with cross-functional teams from hardware to software to provide critical insights for new technologies and solutions. Ideal candidates have a B.Sc in Computer Science or equivalent experience, 5+ years of high-performance networking expertise, proficiency in Python, Bash, C, Linux OS, CUDA, TensorFlow, PyTorch, and NCCL libraries, along with strong analytical skills and knowledge of congestion control algorithms and system architecture.
Skills
Python
C
Bash
CUDA
NCCL
RDMA
MPI
TensorFlow
PyTorch
RoCE
Linux
Intel CPUs
AMD CPUs
ARM CPUs
NVIDIA GPUs
HCA
PCI
Performance Analysis
CI/CD
What you'll do
Profile and analyze AI workloads on large GPU and CPU clusters for distributed deep learning training.
Develop performance analysis tools to identify bottlenecks in high-performance networking.
Implement methodologies to understand performance limitations and optimize collective communications.
Define performance test plans and set expectations for new technologies and solutions.
Collaborate with hardware and software teams to provide insights into performance analysis.
What we're looking for
5+ years experience with high-performance networking technologies (RDMA, MPI, NCCL)
Proficient in performance analysis methodologies and tool development
Expertise in NVIDIA GPUs, CUDA library, and deep learning frameworks like TensorFlow or PyTorch
Strong knowledge of AI workloads and benchmarking for distributed LLM training
Programming skills in Python, Bash, and C languages
Experience with Linux operating systems and various hardware platforms (Intel/AMD/ARM CPUs, GPUs)
Market check
Salary context
This
$152,000–$241,500
range sits above
46%
of similar postings on FindRole.
Peer median band
$155,420–$257,550
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$173,950–$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.
Us, Ca, Santa Clara, US100 days ago
$184,000–$287,500
CUDA
Python
C++
PyTorch
JAX
Warp
HPC
Distributed Learning
Atomistic Modeling
CI/CD
Git
Linux
NVIDIA DGX Systems
GPU Programming
Parallel Computing
Data Structures
Algorithm Design
Machine Learning Frameworks
Scientific AI Codebases
Computational Chemistry
Digital Biology