Senior Software Engineer - Storage
$152k - $288k • Remote • US, CA, Santa Clara
Posted 5d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
NVIDIA's Managed AI Research Superclusters (MARS) team is seeking a Software Engineer to help design, build, and operate exascale infrastructure that powers AI research and development at unprecedented scale. This role involves working on distributed systems, large-scale storage and compute orchestration, and end-to-end automation to enable AI researchers to focus on innovation. You will collaborate with engineers and researchers across NVIDIA to architect reliable, efficient, and secure systems that underpin our Managed AI Research Superclusters, capable of training frontier models and executing global-scale workloads.
Responsibilities
- Design, develop, and operate distributed systems for managing 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 robustness and compliance.
- Participate in design reviews, contribute to system architecture discussions, and influence the evolution of AI infrastructure.
- Stay current with advances in distributed systems, large-scale computing, and AI frameworks.
Requirements
- 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/orchestration (e.g., 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.
Benefits
- Equity
- Benefits