This role pays more than
92%
of similar roles. Most pay
$151,000–$221,100
— the shaded band above.
At the midpoint, this role pays about
$261k
versus about
$186k
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 Senior Staff Platform Engineer, you will join the team to architect, build, and scale foundational infrastructure for demanding compute and AI/ML workloads. You will take end-to-end ownership of highly available platform services, focusing on distributed systems, cloud, networking, storage, and content delivery. Your daily work involves managing DNS, load balancing, proxies, traffic management, and edge infrastructure including HTTP caching and TLS. To achieve these goals, you will utilize Python, Go, Kubernetes, and Terraform to drive automation and infrastructure-as-code. You must possess deep expertise in Linux/Unix, TCP/IP, and fault-tolerant system design while navigating complex problems across cloud, networking, and security domains. This role specifically addresses the technical challenges of supporting large-scale distributed platforms, GPU-accelerated workloads, and high-performance computing environments to ensure reliable infrastructure for data-intensive applications.
What does a Platform Engineer earn?
Median $150000 from 32 postings across 22 companies.
Architect, build, and scale high-availability platform services for AI/ML and distributed compute workloads.
Manage end-to-end ownership of infrastructure from initial design through implementation and large-scale production adoption.
Advance CDN and edge infrastructure including HTTP caching, TLS, WAF, and global load balancing.
Develop automation and self-service capabilities using Python, Go, Kubernetes, and Terraform.
Utilize observability and capacity analytics to improve system reliability, scalability, and operational efficiency.
Design and maintain distributed systems involving networking, storage, DNS, and traffic management.
Solve complex infrastructure problems across cloud, security, and developer infrastructure domains.
What we're looking for
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
12+ years of relevant industry experience.
Proven success architecting, building, and operating large-scale distributed platforms or infrastructure systems in production.
Strong technical depth in cloud infrastructure, distributed systems, networking, compute, storage, platform engineering, or content delivery.
Deep knowledge of Linux/Unix, TCP/IP, DNS, TLS, HTTP/S, proxies, load balancing, availability, scalability, and fault-tolerant system design.
Strong programming skills with Python, Go, or similar languages, plus experience with infrastructure-as-code and orchestration.
Experience with AWS, Azure, or Google Cloud Platform to troubleshoot complex systems across application, operating system, network, and infrastructure layers.
Experience building platforms for AI/ML training, inference, model serving, GPU-accelerated workloads, distributed compute, or high-performance computing (preferred).
Infrastructure as Code
CI/CD
DevSecOps
SAN Storage
Git
Scripting
Cloud Infrastructure
System Administration
Networking
Systems Integration
Performance Monitoring
Automation Frameworks
IT Service Management
Disaster Recovery
Capacity Planning