Senior Storage Production Engineer - DGX Cloud

Nvidia

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $176,000–$276,000 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $194k

This role $226k

$137k most similar roles pay here $291k

This role pays more than 69% of similar roles. Most pay $151,937–$235,750 — the shaded band above. At the midpoint, this role pays about $226k versus about $194k 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 980 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 966 roles with salary data.

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At a glance

TL;DR · Senior Storage Production Engineer - DGX Cloud

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NVIDIA seeks a senior Storage Production Engineer to join its team, responsible for ensuring the reliability and efficiency of large-scale GPU cloud services. This role involves designing and supporting scalable storage clusters, developing monitoring systems, optimizing data access patterns for AI/ML workloads, and implementing automated fault detection mechanisms. The ideal candidate will have extensive experience with distributed storage solutions, proficiency in languages like C/C++, Python, and Bash, and expertise in tools such as Ansible, Terraform, Prometheus, and Grafana. Knowledge of Kubernetes, OpenStack, and hybrid cloud architectures is beneficial, along with a strong background in capacity planning, performance tuning, and troubleshooting high-throughput systems.

Skills

Kubernetes Terraform Python Go Bash Ansible Prometheus Grafana InfluxDB Elasticsearch C/C++ Java NodeJS NFS SMB iSCSI S3 Fibre Channel RDMA NVMe over Fabrics Git CI/CD Docker OpenStack Linux

What you'll do

Design and implement large-scale storage clusters ensuring scalability and high availability.
Develop and maintain monitoring systems to proactively detect and resolve performance issues.
Optimize storage architectures for low-latency access in AI/ML workloads.
Improve lifecycle of storage services from inception to continuous optimization.
Maintain production infrastructure by supervising system health and leveraging predictive analytics.

What we're looking for

BS degree or equivalent in Computer Science with 8+ years of practical experience
Expertise in distributed and high-performance storage solutions and networking protocols
Proficiency in automation tools like Ansible, Terraform, and observability tools
Hands-on experience with C/C++, Python, Go for storage automation and performance tuning
Deep understanding of block, file, and object storage technologies and their characteristics
Experience in capacity planning, performance tuning, and troubleshooting large-scale systems
Knowledge of Kubernetes, OpenStack, and hybrid cloud architectures for automated storage solutions