This role pays more than
52%
of similar roles. Most pay
$159,937–$235,750
— the shaded band above.
At the midpoint, this role pays about
$197k
versus about
$198k
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
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Solutions Architect, Infrastructure, you will join the Solutions Architecture team to lead the deployment and bring-up of next-generation Data Center GPUs and networking platforms for hyperscaler customers. You will serve as a bridge between product strategy, engineering, and large-scale deployments, ensuring alignment across technical and sales organizations while identifying system bottlenecks and operational risks. Your daily work involves solving complex problems involving GPUs, networking, drivers, containers, firmware, and distributed systems. Required expertise includes high-performance networking like RDMA, NVIDIA software stacks including CUDA and NCCL, and Linux tools such as nvidia-smi and ethtool. You must possess a deep understanding of server hardware architecture, PCIe topologies, BIOS/UEFI configurations, and BMC/IPMI/Redfish for remote management. This role addresses the technical challenges of scaling distributed AI workloads across large data center environments.
What does a Solutions Architect earn in California?
Median $235750 from 45 postings across 8 companies.
Provide feedback to Product and Engineering teams to improve platform design, validation, and operational workflows.
What we're looking for
BS/MS/PhD in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a related field, or equivalent experience.
4+ years of experience in Solutions Architecture, Infrastructure Engineering, or similar technical roles.
Hands-on experience with the bring-up and validation of large-scale NVIDIA GPU platforms, including multi-GPU and multi-node architectures.
Understanding of high-performance networking technologies such as RDMA, congestion control, and high-bandwidth interconnects for distributed AI workloads.
Familiarity with NVIDIA system software stacks, including CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning.
Proficiency with Linux systems tools for identifying issues and evaluating performance, such as dmesg, numactl, ethtool, and nvidia-smi.
Understanding of server hardware architecture, including PCIe topologies, firmware, NUMA, BIOS/UEFI configuration, and power/thermal envelopes.
Knowledge of BMC, IPMI, and Redfish for remote management and out-of-band debugging during early-stage bring-up.
Remote (Santa Clara, CA)+143 days ago
$184,000–$287,500
GPU
InfiniBand
RoCE
RDMA
NCCL
NVLink
NVSwitch
Kubernetes
Slurm
Python
Linux
High-Performance Computing
Distributed Systems
Shell Scripting
DCGM
Nsight Systems