Senior Software Engineer - Storage

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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AI @ 4 AWS @ 3 Azure @ 3 Communication @ 6 Compliance @ 3 Distributed Systems @ 6 GCP @ 3 GPU Go @ 7 HPC @ 6 JAX @ 4 Kubernetes @ 4 Leadership @ 6 Machine Learning Networking Observability Performance Optimization @ 6 PyTorch @ 4 Python @ 7 Security @ 3 Slurm @ 4 System Architecture @ 6

Details

NVIDIA's Managed AI Research Superclusters (MARS) team builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop next-generation AI/ML systems. The team is seeking a Software Engineer to help design, build, and operate exascale infrastructure for AI research and development.

The role focuses on distributed systems, large-scale storage and compute orchestration, and end-to-end automation for AI workloads running across multi-region clusters with thousands of GPUs and petabytes of storage.

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.
Improve system reliability, performance, and observability to meet exascale standards.
Partner with security, networking, and platform teams to ensure that MARS infrastructure meets high 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.

Requirements

Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
At least 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 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 technologies such as Lustre, GPFS, or BeeGFS.
Experience with compute scheduling and orchestration technologies such as Slurm, Kubernetes, or LSF.
Familiarity with cloud environments including Azure, AWS, or GCP, as well as infrastructure automation tools.
Strong problem-solving skills, an ownership mindset, and the ability to work in a fast-paced, collaborative environment.
Excellent communication skills and a track record of cross-functional collaboration.

Preferred Qualifications

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 and Benefits

Base salary range of USD 152,000–241,500 for Level 3.
Base salary range of USD 184,000–287,500 for Level 4.
Eligibility for equity and benefits.
The base salary is determined based on location, experience, and the pay of employees in similar positions.
Applications will be accepted at least until October 18, 2026.
This posting is for an existing vacancy.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.