Job description

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.

Requirements

Must-haves

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.
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.
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 .
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythongokubernetesazureawsgcp

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Effort: medium