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NVIDIA

Senior Software Engineer - Storage

AI in this role

pytorchjax
ai-research

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 October 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 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.

How we rate this

Senior Software Engineer - Storage at NVIDIA rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchPyTorchJax

Also common in software engineer jobs at this level

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of Jax that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: AI Research, PyTorch, and Jax. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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