Senior AI and ML Storage Engineer

Details

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. Within this mission, the Managed AI Research Superclusters (MARS) team builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems.

Role overview

You will join the MARS team as a Software Engineer to help design, build, and operate exascale infrastructure that powers AI research and development at unprecedented scale. The role focuses on distributed systems, large-scale storage and compute orchestration, and end-to-end automation to enable AI researchers to focus on innovation rather than infrastructure. You will collaborate across NVIDIA to architect reliable, efficient, and secure systems that underpin Managed AI Research Superclusters capable of training frontier models and executing global-scale workloads.

Responsibilities

• 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 infrastructure meets robustness and compliance requirements.
• 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.

Requirements

• BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
• 8+ 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 (examples: Lustre, GPFS, BeeGFS) and compute scheduling and orchestration (examples: 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.

Ways to stand out

• 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.

Compensation & Additional information

• Base salary ranges (depending on level and location):
  • Level 4: 184,000 USD - 287,500 USD
  • Level 5: 224,000 USD - 356,500 USD
• You will also be eligible for equity and benefits.
• Applications for this job will be accepted at least until October 24, 2025.
• Location specified: Santa Clara, CA, United States. Employment type: Full time.