NVIDIA is seeking to design solutions that power some of the world’s most advanced computing workloads, specifically to build and scale the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems.
Requirements
- 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.
- 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.
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 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.
Other
- 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 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.
