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NVIDIA

Senior Software Engineer – Storage

NVIDIA

. Design, develop, and operate distributed systems that manage data, compute, and networking for large-scale AI workloads .

Posted 10/14/2026full-timeRemote • United StatesSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and operating large-scale distributed systems, with a strong focus on AI workloads and infrastructure automation. Proficient in programming languages such as C++, Python, and Go, and experienced in high-performance storage and orchestration frameworks.

Highest-signal resume keywords
Large-Scale Distributed Systems DevelopmentHigh-Performance Storage ManagementCloud Environments (Azure, AWS, GCP)AI/ML Infrastructure for ResearchSystem Architecture Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
C++ ProgrammingPython ProgrammingGo ProgrammingDistributed Systems PrinciplesData ManagementWorkload Orchestration FrameworksCluster SchedulingPerformance OptimizationReliability EngineeringInfrastructure Automation
Soft Skills
Problem-Solving SkillsOwnership MindsetCollaborationCommunication Skills
Tools & Technologies
LustreGPFSBeeGFSSlurmKubernetesLSFPyTorchJAXNeMo
Certifications & Qualifications
BS in Computer ScienceGraduate Degree (MS/PhD) in Computer Science or Related Field
Industry Keywords
AI WorkloadsExascale StandardsData SecurityComplianceLifecycle Management

Tech Stack

Tools & technologies
AWSAzureCloudDistributed SystemsGoogle Cloud PlatformKubernetesPythonPyTorchC++Go

About the role

Key responsibilities & impact
  • Design, develop, and operate distributed systems that manage data, compute, and networking for large-scale AI workloads
  • Build software and automation to orchestrate workloads across thousands of GPUs and petabytes of storage in multi-region clusters
  • Collaborate with AI/ML research teams to understand requirements and translate them into scalable, high-performance solutions
  • Drive improvements in system reliability, performance, and observability to meet exascale standards
  • Partner with security, networking, and platform teams to ensure MARS infrastructure meets robustness and compliance standards
  • Participate in design reviews, contribute to system architecture discussions, and influence NVIDIA’s AI infrastructure stack
  • Stay current with advances in distributed systems, large-scale computing, and AI frameworks to shape the future direction of MARS

Requirements

What you’ll need
  • BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field
  • 5+ years of experience developing and operating large-scale distributed systems, infrastructure platforms, or HPC environments
  • Strong programming skills in C++, Python, or Go, with proven experience designing production-quality software systems
  • Solid understanding of distributed systems principles, data management, and large-scale orchestration frameworks
  • Hands-on experience with high-performance storage (e.g., Lustre, GPFS, BeeGFS) and compute scheduling and orchestration (e.g., Slurm, Kubernetes, LSF)
  • Familiarity with cloud environments (Azure, AWS, GCP) and infrastructure automation tools
  • Strong problem-solving skills, ownership mindset, and ability to thrive in a fast-paced, collaborative environment
  • Excellent communication skills and a track record of cross-functional collaboration
  • Graduate degree (MS/PhD or equivalent experience) in Computer Science, Distributed Systems, or a related field
  • Expertise in large-scale data management, cluster scheduling, or workload orchestration at exascale scale
  • Experience building or maintaining infrastructure for AI/ML research, including distributed training pipelines using PyTorch, JAX, or NeMo
  • Familiarity with data security, compliance, and lifecycle management for research-scale datasets
  • Demonstrated leadership in system architecture design, performance optimization, or reliability engineering

Benefits

Comp & perks
  • Equity
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