Senior Site Reliability Storage Engineer - GPU Clusters

NVIDIA
Full_time•$184k-357k/year (USD)•Redmond, United States

📍 Job Overview

  • Job Title: Senior Site Reliability Storage Engineer - GPU Clusters
  • Company: NVIDIA
  • Location: Santa Clara, California, United States (Remote: Redmond, Washington, United States; Seattle, Washington, United States)
  • Job Type: Full-Time
  • Category: DevOps, Infrastructure
  • Date Posted: 2025-07-30
  • Experience Level: 5-10 years
  • Remote Status: On-site with remote options

🚀 Role Summary

  • Design, deploy, and manage high-speed storage solutions for large-scale GPU clusters powering AI workloads across multiple teams and projects.
  • Collaborate with researchers, AI engineers, and infrastructure teams to ensure GPU clusters perform efficiently, scale well, and remain reliable.
  • Evolve private/public cloud strategy, capacity modeling, and growth planning across the global computing environment.
  • Drive the evaluation and integration of storage solutions with new GPU technologies and cloud services to improve system performance.

📝 Enhancement Note: This role requires a strong background in storage solutions, cloud environments, and distributed filesystems to succeed in a dynamic, high-performance computing environment.

💻 Primary Responsibilities

  • Storage Solutions Architecture: Design and implement scalable, efficient storage solutions tailored for data-intensive AI applications, optimizing performance and cost-effectiveness.
  • Cloud Environment Management: Support globally distributed on-premise and cloud environments like AWS, GCP, Azure, or OCI.
  • Storage Infrastructure Provisioning: Continuously improve storage infrastructure provisioning, management, observability, and day-to-day operation through automation.
  • Incident Resolution & Root Cause Analysis: Ensure the highest level of uptime and quality of service (QoS) through operational excellence, proactive monitoring, and incident resolution. Write high-quality RCA reports for production-level incidents and work towards preventing future occurrences.
  • Researcher Support: Support researchers to run their flows on clusters, including performance analysis and optimizations of deep learning workflows.
  • Service Level Objectives & Indicators: Define and implement service level objectives (SLOs) and service level indicators (SLIs) to measure and ensure infrastructure quality.
  • Strategic Planning: Drive the evaluation and integration of storage solutions with new GPU technologies and cloud services to improve system performance and stay ahead of emerging trends.

📝 Enhancement Note: This role requires a proactive approach to problem-solving, strong communication skills, and the ability to work effectively in a multi-cloud environment.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science or a related field. Relevant work experience may be considered in lieu of a degree.

Experience: 6+ years managing high-speed storage solutions deployed for GPU clusters or similar high-performance computing environments.

Required Skills:

  • Expertise in designing, deploying, and running production-level cloud services.
  • Experience with one or more parallel or distributed filesystems such as Lustre, GPFS, including experience analyzing and tuning performance for a variety of AI/HPC workloads.
  • Experience with architecture design and operation of storage solutions on leading cloud environments (AWS, Azure, or GCP).
  • Proficiency with orchestration and containerization tools like Kubernetes, Docker, or similar.
  • Experience coding/scripting in at least two high-level programming languages (e.g., Python, Go, Ruby).
  • Proficient in modern CI/CD techniques and Infrastructure as Code (IaC) using tools such as Terraform or Ansible.
  • Diligent with strong communication and documentation skills.

Preferred Skills:

  • Experience running large-scale Slurm/LSF and/or BCM deployments in production environments.
  • Expertise in modern container networking and storage architecture.
  • Experience with Machine Learning and Deep Learning concepts, algorithms, and models.
  • Consistent record of defining and driving operational excellence in highly distributed, high-performance environments.

📝 Enhancement Note: Candidates with experience in large-scale storage solutions, cloud environments, and distributed filesystems will be well-positioned to succeed in this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

  • Demonstrate experience in designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  • Showcase projects that highlight your ability to optimize storage performance for AI workloads and improve system efficiency.
  • Include case studies or examples of your work in cloud environments, distributed filesystems, and containerization tools.

Technical Documentation:

  • Provide documentation detailing your approach to storage infrastructure provisioning, management, and day-to-day operation through automation.
  • Include examples of your work in defining and implementing service level objectives (SLOs) and service level indicators (SLIs).
  • Showcase your ability to write high-quality root cause analysis (RCA) reports for production-level incidents and demonstrate your commitment to preventing future occurrences.

📝 Enhancement Note: A strong portfolio showcasing your experience in storage solutions, cloud environments, and distributed filesystems will be crucial for success in this role.

💵 Compensation & Benefits

Salary Range: The base salary range is $184,000 USD - $356,500 USD per year, depending on location, experience, and the pay of employees in similar positions.

Benefits:

  • Equity
  • Comprehensive Benefits Package

Working Hours: Full-time position with a standard 40-hour workweek. Flexible hours may be required to support maintenance windows and project deadlines.

📝 Enhancement Note: The provided salary range is based on NVIDIA's internal pay scales and may vary depending on the candidate's location, experience, and the pay of employees in similar positions.

🎯 Team & Company Context

🏢 Company Culture

Industry: NVIDIA operates in the technology industry, focusing on graphics processing units (GPUs) and artificial intelligence (AI) technologies. This role will have a significant impact on the future of machine learning and AI at NVIDIA.

Company Size: NVIDIA is a large, established company with a global presence, providing ample opportunities for collaboration and growth.

Founded: NVIDIA was founded in 1993 and has since grown to become a leading innovator in GPU technology.

Team Structure:

  • The team consists of experienced engineers, researchers, and infrastructure specialists working together to ensure the efficient, scalable, and reliable performance of GPU clusters.
  • The role will collaborate with researchers, AI engineers, and infrastructure teams to drive storage solutions and improve system performance.

Development Methodology:

  • Agile methodologies are used to manage projects and ensure efficient collaboration between teams.
  • Code reviews, testing, and quality assurance practices are employed to maintain high coding standards and ensure the reliability of storage solutions.
  • Deployment strategies, CI/CD pipelines, and server management are crucial aspects of this role, requiring a strong understanding of modern development practices.

Company Website: NVIDIA

📝 Enhancement Note: NVIDIA's culture emphasizes innovation, collaboration, and a passion for technology. This role will allow you to work with cutting-edge GPU technologies and make a significant impact on the future of AI at NVIDIA.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior level, requiring significant experience in storage solutions, cloud environments, and distributed filesystems. The ideal candidate will have a proven track record of driving operational excellence and improving system performance in highly distributed, high-performance environments.

Reporting Structure: This role will report directly to the manager of the GPU cluster infrastructure team and collaborate with researchers, AI engineers, and other infrastructure teams to ensure the efficient performance of GPU clusters.

Technical Impact: The role will have a significant impact on the performance, scalability, and reliability of GPU clusters powering AI workloads across multiple teams and projects. The ideal candidate will be passionate about driving operational excellence and staying ahead of emerging trends in storage solutions and cloud technologies.

Growth Opportunities:

  • Technical Growth: Expand your expertise in storage solutions, cloud environments, and distributed filesystems by working on cutting-edge GPU technologies and collaborating with experienced engineers and researchers.
  • Leadership Potential: Demonstrate your ability to drive operational excellence and improve system performance to take on more significant responsibilities within the team or across the organization.
  • Architecture Decisions: Contribute to strategic decisions regarding storage solutions, cloud technologies, and the evolution of NVIDIA's private/public cloud strategy.

📝 Enhancement Note: This role offers ample opportunities for growth and development within NVIDIA's dynamic and innovative environment.

🌐 Work Environment

Office Type: NVIDIA's offices are designed to foster collaboration and innovation, with state-of-the-art facilities and a focus on employee comfort and well-being.

Office Location(s): Santa Clara, California, United States (Remote: Redmond, Washington, United States; Seattle, Washington, United States)

Workspace Context:

  • Collaborative Environment: Work closely with researchers, AI engineers, and infrastructure teams to ensure the efficient performance of GPU clusters.
  • Development Tools: Access to modern development tools, multiple monitors, and testing devices to support your work in designing, deploying, and managing high-speed storage solutions.
  • Cross-Functional Collaboration: Collaborate with designers, marketers, and other stakeholders to ensure storage solutions meet the needs of AI workloads and improve system performance.

Work Schedule: Full-time position with a standard 40-hour workweek. Flexible hours may be required to support maintenance windows, incident resolution, and project deadlines.

📝 Enhancement Note: NVIDIA's work environment encourages collaboration, innovation, and a passion for technology, providing an ideal setting for professionals seeking to grow their careers in storage solutions and cloud technologies.

📄 Application & Technical Interview Process

Interview Process:

  • Technical Assessment: Demonstrate your expertise in storage solutions, cloud environments, and distributed filesystems through technical assessments and case studies.
  • Architecture Discussion: Discuss your approach to storage solutions architecture, cloud technologies, and the evolution of NVIDIA's private/public cloud strategy.
  • Team Interaction: Collaborate with researchers, AI engineers, and infrastructure teams to ensure the efficient performance of GPU clusters and drive operational excellence.
  • Final Evaluation: Showcase your ability to make strategic decisions regarding storage solutions, cloud technologies, and the future of AI at NVIDIA.

Portfolio Review Tips:

  • Storage Solutions Focus: Highlight your experience in designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  • Cloud Environment Expertise: Demonstrate your ability to work effectively in multi-cloud environments and optimize storage performance for AI workloads.
  • Documentation & RCA: Showcase your ability to write high-quality documentation and root cause analysis (RCA) reports for production-level incidents.

Technical Challenge Preparation:

  • Storage Solutions Architecture: Brush up on your knowledge of storage solutions architecture, cloud technologies, and distributed filesystems to prepare for technical assessments and case studies.
  • Incident Resolution: Familiarize yourself with incident resolution processes and best practices to ensure the highest level of uptime and quality of service (QoS) for GPU clusters.
  • Strategic Planning: Prepare for discussions on the evolution of NVIDIA's private/public cloud strategy and the future of AI at NVIDIA.

ATS Keywords: (See the comprehensive list of web development and server administration-relevant keywords for resume optimization, organized by category, at the end of this document.)

📝 Enhancement Note: NVIDIA's interview process is designed to assess your technical expertise, strategic thinking, and ability to collaborate with researchers, AI engineers, and infrastructure teams to drive operational excellence and improve system performance.

🛠 Technology Stack & Web Infrastructure

Storage Technologies:

  • Lustre
  • GPFS
  • AWS, Azure, or GCP cloud environments

Containerization Tools:

  • Kubernetes
  • Docker

Programming Languages:

  • Python
  • Go
  • Ruby

Infrastructure as Code (IaC) Tools:

  • Terraform
  • Ansible

Monitoring Tools:

  • Prometheus
  • Grafana

📝 Enhancement Note: Familiarity with these storage technologies, containerization tools, programming languages, IaC tools, and monitoring tools will be crucial for success in this role.

👥 Team Culture & Values

NVIDIA Values:

  • Innovation: NVIDIA values innovation and encourages employees to push the boundaries of what's possible in GPU technology and AI.
  • Collaboration: NVIDIA fosters a culture of collaboration, encouraging employees to work together to achieve common goals and drive operational excellence.
  • Perseverance: NVIDIA values perseverance and expects employees to approach challenges with determination and a commitment to finding solutions.

Collaboration Style:

  • Cross-Functional Integration: Work closely with researchers, AI engineers, and other teams to ensure the efficient performance of GPU clusters and drive operational excellence.
  • Code Review Culture: Participate in code reviews and contribute to the maintenance of high coding standards within the team.
  • Knowledge Sharing: Share your expertise in storage solutions, cloud environments, and distributed filesystems with team members and contribute to the growth of the team's collective knowledge.

📝 Enhancement Note: NVIDIA's culture values innovation, collaboration, and perseverance, providing an ideal environment for professionals seeking to grow their careers in storage solutions and cloud technologies.

⚡ Challenges & Growth Opportunities

Technical Challenges:

  • Storage Solutions Architecture: Design and implement scalable, efficient storage solutions tailored for data-intensive AI applications, optimizing performance and cost-effectiveness.
  • Cloud Environment Management: Support globally distributed on-premise and cloud environments, ensuring the efficient performance of GPU clusters and driving operational excellence.
  • Incident Resolution & RCA: Ensure the highest level of uptime and quality of service (QoS) for GPU clusters through operational excellence, proactive monitoring, and incident resolution. Write high-quality RCA reports for production-level incidents and work towards preventing future occurrences.

Learning & Development Opportunities:

  • Technical Skill Development: Expand your expertise in storage solutions, cloud environments, and distributed filesystems by working on cutting-edge GPU technologies and collaborating with experienced engineers and researchers.
  • Conference Attendance & Certification: Attend industry conferences and pursue relevant certifications to stay up-to-date with emerging trends in storage solutions and cloud technologies.
  • Technical Mentorship & Leadership Development: Contribute to the growth of the team's collective knowledge and take on mentorship roles to help junior team members develop their skills and advance their careers.

📝 Enhancement Note: This role offers ample opportunities for growth and development within NVIDIA's dynamic and innovative environment, with a focus on driving operational excellence and improving system performance.

💡 Interview Preparation

Technical Questions:

  • Storage Solutions Architecture: Discuss your approach to designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  • Cloud Environment Management: Explain your experience working with cloud environments like AWS, Azure, or GCP and how you've optimized storage performance for AI workloads.
  • Incident Resolution & RCA: Describe your process for ensuring the highest level of uptime and quality of service (QoS) for GPU clusters and your approach to writing high-quality RCA reports for production-level incidents.

Company & Culture Questions:

  • NVIDIA's Storage Solutions Strategy: Research NVIDIA's approach to storage solutions and discuss how your experience aligns with the company's strategic goals.
  • AI Workload Optimization: Explain your understanding of AI workloads and how you've optimized storage performance to support deep learning workflows and improve system efficiency.
  • Team Collaboration: Describe your experience working with researchers, AI engineers, and infrastructure teams to drive operational excellence and ensure the efficient performance of GPU clusters.

Portfolio Presentation Strategy:

  • Storage Solutions Focus: Highlight your experience in designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  • Cloud Environment Expertise: Demonstrate your ability to work effectively in multi-cloud environments and optimize storage performance for AI workloads.
  • Documentation & RCA: Showcase your ability to write high-quality documentation and root cause analysis (RCA) reports for production-level incidents.

📝 Enhancement Note: Prepare thoroughly for NVIDIA's interview process, focusing on your technical expertise, strategic thinking, and ability to collaborate with researchers, AI engineers, and infrastructure teams to drive operational excellence and improve system performance.

📌 Application Steps

To apply for this Senior Site Reliability Storage Engineer - GPU Clusters position at NVIDIA:

  1. Customize Your Portfolio: Tailor your portfolio to showcase your experience in storage solutions, cloud environments, and distributed filesystems, with a focus on designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  2. Optimize Your Resume: Highlight your relevant skills and experience in storage solutions, cloud environments, and distributed filesystems, and emphasize your ability to drive operational excellence and improve system performance.
  3. Prepare for Technical Interviews: Brush up on your knowledge of storage solutions architecture, cloud technologies, and distributed filesystems, and practice incident resolution processes and best practices to ensure the highest level of uptime and quality of service (QoS) for GPU clusters.
  4. Research NVIDIA: Familiarize yourself with NVIDIA's approach to storage solutions, cloud technologies, and the future of AI at the company to ensure a strong fit with the team's goals and culture.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

  • Tailor every section specifically to storage solutions, cloud environments, and distributed filesystems, with a focus on designing, deploying, and managing high-speed storage solutions for GPU clusters or similar high-performance computing environments.
  • Include web technology methodologies, cloud services, and distributed filesystems relevant to the role.
  • Emphasize storage infrastructure provisioning, management, observability, and day-to-day operation through automation.
  • Address incident resolution processes, root cause analysis (RCA), and service level objectives (SLOs) and service level indicators (SLIs).
  • Highlight the role's impact on AI workloads, deep learning workflows, and the future of machine learning and artificial intelligence at NVIDIA.

Quality Standards:

  • Ensure no content overlap between sections - each section must contain unique information.
  • Only include Enhancement Notes when making significant inferences about technical responsibilities, storage solutions architecture, or team structure.
  • Be comprehensive but concise, prioritizing actionable information over descriptive text.
  • Strategically distribute storage solutions, cloud environments, and distributed filesystems-related keywords throughout all sections naturally.
  • Provide realistic salary ranges based on location, experience level, and web technology specialization.

Industry Expertise:

  • Include specific storage technologies, cloud environments, and distributed filesystems relevant to the role.
  • Address storage solutions architecture design and operation on leading cloud environments (AWS, Azure, or GCP).
  • Provide tactical advice for portfolio development, live demonstrations, and project case studies focused on storage solutions, cloud environments, and distributed filesystems.
  • Include storage solutions-specific interview preparation and coding challenge guidance.
  • Emphasize storage solutions, cloud environments, and distributed filesystems-specific interview process insights and tactical advice for technical interviews.

Professional Standards:

  • Maintain consistent formatting, spacing, and professional tone throughout.
  • Use storage solutions, cloud environments, and distributed filesystems industry terminology appropriately and accurately.
  • Include comprehensive benefits and growth opportunities relevant to storage solutions, cloud environments, and distributed filesystems professionals.
  • Provide actionable insights that give storage solutions, cloud environments, and distributed filesystems candidates a competitive advantage.
  • Focus on storage solutions, cloud environments, and distributed filesystems team culture, cross-functional collaboration, and user impact measurement.

Technical Focus & Portfolio Emphasis:

  • Emphasize storage solutions architecture design, cloud services, and distributed filesystems best practices.
  • Include specific portfolio requirements tailored to the storage solutions, cloud environments, and distributed filesystems discipline and role level.
  • Address browser compatibility, accessibility standards, and user experience design principles relevant to storage solutions, cloud environments, and distributed filesystems.
  • Focus on problem-solving methods, performance optimization, and scalable storage architecture.
  • Include technical presentation skills and stakeholder communication for storage solutions, cloud environments, and distributed filesystems projects.

Avoid:

  • Generic business jargon not relevant to storage solutions, cloud environments, and distributed filesystems roles.
  • Placeholder text or incomplete sections.
  • Repetitive content across different sections.
  • Non-technical terminology unless relevant to the specific storage solutions, cloud environments, and distributed filesystems role.
  • Marketing language unrelated to storage solutions, cloud environments, and distributed filesystems.

ATS Keywords:

Programming Languages:

  • Python
  • Go
  • Ruby

Storage Technologies:

  • Lustre
  • GPFS
  • AWS, Azure, or GCP cloud environments

Containerization Tools:

  • Kubernetes
  • Docker

Infrastructure as Code (IaC) Tools:

  • Terraform
  • Ansible

Monitoring Tools:

  • Prometheus
  • Grafana

Cloud Environment Keywords:

  • AWS
  • Azure
  • GCP
  • Cloud Services
  • Multi-Cloud Environment
  • Cloud Infrastructure
  • Cloud Provisioning
  • Cloud Management
  • Cloud Migration
  • Cloud Security

Distributed Filesystems Keywords:

  • Lustre
  • GPFS
  • Ceph
  • GlusterFS
  • Distributed Storage
  • Parallel Filesystems
  • High-Performance Computing (HPC)
  • High-Speed Storage
  • Storage Performance
  • Storage Scalability
  • Storage Capacity

Incident Resolution & RCA Keywords:

  • Incident Management
  • Root Cause Analysis (RCA)
  • Proactive Monitoring
  • Uptime
  • Quality of Service (QoS)
  • Mean Time to Recovery (MTTR)
  • Mean Time to Acknowledge (MTTA)
  • Mean Time to Resolution (MTR)
  • Service Level Agreement (SLA)
  • Service Level Objective (SLO)
  • Service Level Indicator (SLI)

Web Technology Industry Context:

  • AI Workloads
  • Deep Learning Workflows
  • Machine Learning
  • Artificial Intelligence (AI)
  • GPU Clusters
  • High-Performance Computing (HPC)
  • Data-Intensive Applications
  • Cloud-Native Architecture
  • Microservices
  • Containerization
  • Orchestration
  • Automation
  • Infrastructure as Code (IaC)
  • Continuous Integration/Continuous Deployment (CI/CD)
  • Agile Methodologies
  • Scrum
  • Kanban
  • DevOps
  • Site Reliability Engineering (SRE)
  • Infrastructure as a Service (IaaS)
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)
  • Serverless Architecture
  • Container Orchestration
  • Kubernetes
  • Docker
  • Serverless Framework
  • AWS Lambda
  • Azure Functions
  • Google Cloud Functions

Application Requirements

Candidates should have a minimum of a BS degree in Computer Science and 6+ years of experience managing high-speed storage solutions. Expertise in cloud environments and distributed filesystems is essential.