This role pays more than
90%
of similar roles. Most pay
$146,395–$213,375
— the shaded band above.
At the midpoint, this role pays about
$236k
versus about
$180k
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.
The NCX Senior Engineer joins the DSX team to manage and improve operational capabilities for large-scale NVIDIA accelerated infrastructure in production. This role focuses on guiding NVIDIA Cloud Partners through Day 2 operations, including infrastructure health, observability, lifecycle management, and automated remediation. You will build continuous validation systems for GPU, CPU, storage, and network components while developing telemetry, monitoring, and alerting across Kubernetes and InfiniBand/RoCE networking environments. Key responsibilities include managing firmware lifecycles, OS patching, and translating reference architectures into production runbooks. The ideal candidate possesses expertise in Linux-based distributed systems, cloud infrastructure, and site reliability engineering. Required technical skills include proficiency in Python, Go, or shell scripting to automate infrastructure management. This role addresses the complex challenge of maintaining reliable performance for large-scale AI training and inference workloads across diverse partner environments.
Lead Day 2 operational readiness efforts for NVIDIA Cloud Partners to manage large-scale accelerated infrastructure.
Develop and implement methods to continuously validate GPU, CPU, storage, and network health across AI clusters.
Establish comprehensive observability, monitoring, alerting, and dashboards for compute, networking, and Kubernetes workloads.
Build automated workflows to detect, isolate, repair, and remediate unhealthy infrastructure while minimizing service disruption.
Manage fleet lifecycle administration including firmware updates, driver management, OS patching, and configuration drift identification.
Translate NVIDIA reference architectures into production operating practices, runbooks, and measurable operational standards.
Develop reusable tools, automation scripts, and implementation guides for consistent application across multiple partner environments.
Define operational health metrics, SLOs, and acceptance criteria to provide clear insight into infrastructure reliability.
What we're looking for
BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
8+ years of experience in infrastructure engineering, Site Reliability Engineering, DevOps, cloud platform engineering, systems engineering, or similar roles.
Strong experience operating Linux-based distributed systems and cloud infrastructure in production environments.
Deep understanding of Kubernetes, containers, cluster scheduling, and the operational lifecycle of large multi-node environments.
Strong understanding of production observability including metrics, logging, alerting, dashboards, health checks, and service level agreements.
Experience crafting automation for infrastructure lifecycle management, failure detection, remediation, upgrades, and configuration management.
Strong networking fundamentals and experience troubleshooting complex distributed systems across compute, network, and storage layers.
Programming and automation experience using Python, Go, shell scripting, or similar languages.
Remote (Santa Clara, CA)+18 days ago
$184,000–$287,500
Kubernetes
Python
Go
PyTorch
TensorFlow
CUDA
MLOps
Terraform
Ansible
Prometheus
Grafana
InfiniBand
RoCE
Triton
NeMo
CI/CD
Linux
Distributed Systems
NVIDIA Reference Architectures
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
GNC
MATLAB
Simulink
Python
C++
Go
Linux
Orbital Mechanics
Control Theory
Computer Vision
Hardware-in-the-Loop
monte-carlo simulation
Spacecraft Dynamics
Flight Software