AI Insights
NVIDIA

Senior Software Engineer - Storage

NVIDIA · Santa Clara, California, US
full-timesenior (5-12 yrs)Posted 41d ago
Software EngineeringIC3ICOn-site
StackC++PythonGoLustreGPFSBeeGFSSlurmKubernetesLSFAzureAWSGCPPyTorchJAXNeMoDistributed SystemsHPCInfrastructure Automation

Summary

NVIDIA's Managed AI Research Superclusters (MARS) team is hiring a Senior Software Engineer to design, build, and operate exascale distributed infrastructure supporting AI/ML research workloads across thousands of GPUs and petabytes of storage.

About the role

NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Research Superclusters (MARS), builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads.

We are seeking a Software Engineer to join our MARS team at NVIDIA. In this role, you will help design, build, and operate exascale infrastructure that powers AI research and development at unprecedented scale. You will work on distributed systems, large-scale storage and compute orchestration, and end-to-end automation that enable AI researchers to focus on innovation rather than infrastructure. You will collaborate closely with engineers and researchers across NVIDIA to architect reliable, efficient, and secure systems that underpin our Managed AI Research Superclusters — infrastructure capable of training frontier models and executing global-scale workloads.

What You’ll Be Doing:

  • 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 their 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 that MARS infrastructure meets the highest standards of robustness and compliance.

  • Participate in design reviews, contribute to system architecture discussions, and influence the evolution of NVIDIA’s AI infrastructure stack.

  • Stay current with advances in distributed systems, large-scale computing, and AI frameworks to help shape the future direction of MARS.

What We Need to See:

  • 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 the ability to thrive in a fast-paced, collaborative environment.

  • Excellent communication skills and a track record of cross-functional collaboration.

Ways to Stand Out from the Crowd:

  • 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What you'll do

1Design, develop, and operate distributed systems managing data, compute, and networking for large-scale AI workloads
2Build software and automation to orchestrate workloads across thousands of GPUs and petabytes of storage in multi-region clusters
3Collaborate with AI/ML research teams to translate requirements into scalable, high-performance infrastructure solutions
4Drive improvements in system reliability, performance, and observability to meet exascale standards
5Partner with security, networking, and platform teams to ensure robustness and compliance of MARS infrastructure
6Participate in design reviews and contribute to system architecture discussions influencing NVIDIA's AI infrastructure stack
7Stay current with advances in distributed systems, large-scale computing, and AI frameworks

Requirements

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
Hands-on experience with high-performance storage systems (Lustre, GPFS, BeeGFS) and compute scheduling/orchestration (Slurm, Kubernetes, LSF)
Solid understanding of distributed systems principles, data management, and large-scale orchestration frameworks
Familiarity with cloud environments (Azure, AWS, GCP) and infrastructure automation tools

Nice to have

PyTorch
JAX
NeMo
Distributed training pipelines
Data security and compliance
Workload orchestration at exascale
Graduate degree (MS/PhD) in Computer Science or Distributed Systems
Performance optimization
Reliability engineering

Role overview

Role family
Software Engineering
Level
IC3 — platform
Experience
5–12 years
Type
Individual Contributor
Remote policy
On-site
Visa sponsorship
Not offered

Tech stack analysis

LANGUAGES
C++PythonGo
FRAMEWORKS
PyTorchJAXNeMo
INFRASTRUCTURE
KubernetesSlurmLSFAzureAWSGCPLustreGPFSBeeGFS
TOOLS
Infrastructure automation tools (unspecified)

Green flags

6 items
Salary range explicitly disclosed with level breakdowns ($152K–$287.5K), which is rare and highly transparent.compensation

Discover all 6 green flags for this role

Sign up free →

Benefits breakdown

See all benefits organized by category — health, financial, time off & more

Sign up free →

Hiring insights

JD quality
8/10
Urgency
medium
Autonomy
high
Team size
medium (5-15)

See JD quality score, hiring urgency & team details

Sign up free →

Red flags

PRO3 items
Exascale infrastructure operations at a high-velocity AI company imply potential on-call responsibilities and high operational demands, though not explicitly stated.work life balance

See all 3 red flags — what the JD isn't telling you

Sign up free →

Interview insights

PRO
Rounds
5
Duration
4 wks
Difficulty
very hard
Take-home
No

Get full interview breakdown — rounds, likely topics & prep tips

Sign up free →

Career path

PRO
Next roles
Staff Software EngineerPrincipal Engineer (Infrastructure)Engineering Manager (Infrastructure)

See where this role leads — full career progression

Sign up free →
About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Interview difficultyvery hard
Build vs Maintainboth
Cross-functionalYes