Senior Software Engineer - DGX Cloud
About The Position
Join NVIDIA’s DGX Cloud team to scale the AI infrastructure powering advanced data science applications. The team addresses challenges across datacenter hardware, networking, distributed systems, and software deployment, collaborating with engineering teams across NVIDIA to design and deliver infrastructure that supports AI-based systems at scale. The role contributes to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers. It also builds end-to-end automation for datacenter management and system upkeep, and develops monitoring, health management, and automated test capabilities to support reliable, available, and scalable GPU assets and distributed systems.
Requirements
- 12+ years of experience in a similar role working on large-scale production systems.
- Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or a comparable field, or equivalent experience.
- Expert-level knowledge of a systems programming language such as Go, Python, and/or Rust.
- 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 datacenter management, break/fix, and system upkeep for large-scale machine learning systems.
- Implement monitoring and health management capabilities for GPU asset reliability, availability, and scalability.
- Use data streams including GPU hardware diagnostics and cluster and network telemetry.
- Build automated test infrastructure to qualify distributed systems for operation.
- Partner with NVIDIA engineering teams to integrate software from hardware through AI training applications.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
