Senior Software Engineer - DGX Cloud
About The Position
Join a team of engineers at NVIDIA dedicated to scaling the AI infrastructure that powers cutting-edge data science applications. The team solves complex challenges across datacenter hardware, networking, distributed systems, and software deployment, collaborating closely to design and deliver leading infrastructure solutions. It values strong technical foundations, creative thinking, and a bias toward execution, while continuously pushing boundaries and advancing NVIDIA’s ability to build and deploy AI-based infrastructure at scale. The role contributes to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers. It builds end-to-end data center management and system upkeep automation for large-scale Machine Learning systems, along with monitoring, health management, and automated test infrastructure to qualify distributed systems. The engineer partners with teams across NVIDIA to ensure software integrates from hardware through AI training applications.
Requirements
- 12+ years of experience in a similar role working on large-scale production systems.
- BS in Computer Science, Engineering, Physics, Mathematics, or a comparable degree, or equivalent experience.
- Expert-level knowledge of a systems programming language such as Go, Python, and/or Rust, and a solid understanding of data structures and algorithms.
- Strong background in Linux system administration and management.
- Deep knowledge of container orchestration platforms such as Kubernetes and/or SLURM.
- Understanding of performance, security, and reliability in complex distributed systems.
- Familiarity with system-level architecture, data synchronization, fault tolerance, and state management.
Nice To Haves
- Proficiency in designing and building widespread distributed networks.
- Experience managing large-scale distributed systems independently of cloud providers.
- Extensive expertise in datacenter operations and GPU hardware.
- Hands-on experience working with RDMA networking.
- Advanced hands-on experience and deep understanding of cluster management systems such as Kubernetes and SLURM.
Responsibilities
- Contribute to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.
- Build end-to-end automation for data center management, break/fix, and system upkeep for large-scale Machine Learning systems.
- Implement monitoring and health management capabilities to support reliability, availability, and scalability of GPU assets.
- Use data streams that include GPU hardware diagnostics, cluster telemetry, and network telemetry.
- Build automated test infrastructure to qualify distributed systems for operation.
- Partner with engineering teams across NVIDIA to ensure software integrates from hardware through AI training applications.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
