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.
You will also be eligible for equity and benefits.
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.Skills Required
- BS or equivalent experience in Computer Science, Computer Engineering, or related technical field
- 5+ years developing and operating large-scale distributed systems, infrastructure platforms, or HPC environments
- Strong programming skills in C++, Python, or Go with production-quality software experience
- Solid understanding of distributed systems principles, data management, and large-scale orchestration frameworks
- Hands-on experience with high-performance storage (Lustre, GPFS, BeeGFS) and compute scheduling/orchestration (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 fast-paced collaborative environments
- Excellent communication skills and track record of cross-functional collaboration
- Graduate degree (MS/PhD) in Computer Science, Distributed Systems, or related field
- Expertise in large-scale data management, cluster scheduling, or workload orchestration at exascale
- Experience building or maintaining infrastructure for AI/ML research, including distributed training pipelines (PyTorch, JAX, NeMo)
- Familiarity with data security, compliance, and lifecycle management for research-scale datasets
- Demonstrated leadership in system architecture design, performance optimization, or reliability engineering
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
