Senior Storage Production Engineer - DGX Cloud

at Nvidia

📍 Santa Clara, United States

USD 176,000-333,500 per year

SENIOR

✅ On-site

Used Tools & Technologies

IaC Machine Learning

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Security @ 4 Ansible @ 4 Chef @ 4 Go @ 4 Grafana @ 4 Kubernetes @ 4 Linux @ 4 Prometheus @ 4 Terraform @ 4 Python @ 4 Java @ 4 CI/CD @ 4 Algorithms @ 4 Data Structures @ 4 Bash @ 4 Communication @ 7 Git @ 4 Networking @ 4 OpenStack @ 4 Prioritization @ 4 Debugging @ 7 Puppet @ 4 Compliance @ 4 Observability @ 4 AI @ 4 HPC @ 4

Details

Production engineering is focused on building and maintaining large-scale production systems with high efficiency and availability. This role emphasizes storage architecture, high-performance distributed storage, data management, systems, networking, coding, database management, prioritization, continuous delivery and deployment, and cloud-enabling technologies such as Kubernetes, containers, and virtualization. Storage Production Engineers ensure storage architectures are reliable, scalable, and efficient, optimize data placement and access patterns, manage large-scale distributed storage systems, and ensure low-latency data access for HPC and AI/ML workloads.

Responsibilities

Design, implement, and support large-scale storage clusters ensuring scalability, high availability, and data integrity.
Develop and maintain storage monitoring, logging, and alerting systems to ensure proactive detection and resolution of performance issues.
Work with AI/ML workloads to improve storage architectures for low-latency access, efficient caching, and high-throughput performance.
Improve the lifecycle of storage services from inception and design to deployment, operation, and continuous optimization; support storage services before launch (system build consulting, automation frameworks, capacity management, launch reviews).
Maintain production storage infrastructure by supervising availability, latency, and system health, leveraging predictive analytics and AI-driven automation.
Optimize storage efficiency through compression, deduplication, tiering strategies, and intelligent workload placement.
Scale storage systems using AI/ML-driven automation, policy-based tiering, and dynamic data migration techniques; ensure data security and compliance (encryption, access controls, auditing).
Practice sustainable incident response and blameless root cause analysis; participate in an on-call rotation to support storage and production systems.

Requirements

BS degree or equivalent experience in Computer Science, Storage Systems, or a related technical field with 8+ years of practical experience.
Experience with distributed and high-performance storage solutions, including clustered and parallel file systems, distributed object storage, and enterprise-grade storage systems.
Solid understanding of block, file, and object storage technologies, including scalability, reliability, and performance characteristics.
Experience with storage networking protocols such as NFS, SMB, iSCSI, S3, Fibre Channel, RDMA, and NVMe over Fabrics.
Expertise in algorithms, data structures, complexity analysis, software design, and automating maintenance of large-scale Linux-based storage systems.
Experience in one or more programming languages for storage automation, monitoring, and performance tuning: C/C++, Java, Python, Go, NodeJS, and Bash.
Hands-on experience with infrastructure configuration management tools like Ansible, Chef, Puppet, and Terraform for automating storage deployments.
Experience with observability and tracing tools such as InfluxDB, Prometheus, Grafana, and the Elastic stack for monitoring storage system health.
Strong written and oral communication skills, teamwork, work ethic, and commitment to producing quality work.

Ways to Stand Out

Deep understanding of large distributed storage systems, replication strategies, and erasure coding techniques; experience in capacity planning, performance tuning, and troubleshooting high-throughput storage systems.
Experience with Git, code review, pipelines, and CI/CD for infrastructure as code.
Experience with private and public cloud storage solutions based on Kubernetes, OpenStack, or hybrid cloud architectures.
Ability to design and implement automated storage migration, backup, and disaster recovery strategies.
Strong debugging skills and systematic problem-solving approach; proven understanding of network protocols and troubleshooting techniques related to storage performance, stability, and availability.

Compensation & Benefits

Base salary is determined based on location, experience, and pay of employees in similar positions.
Base salary ranges provided: 176,000 USD - 276,000 USD for Level 4; 208,000 USD - 333,500 USD for Level 5.
Eligible for equity and benefits (link to NVIDIA benefits).

Applications for this job will be accepted at least until June 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer; they do not discriminate on the basis of characteristics protected by law.