Role at a glance
- Job function
-
Software Engineering & IT Software Engineering
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Santa Clara, California, United States
- Employment
- Full-time
- Experience
- Senior Level 12+ years of experience in a similar role working on large-scale production systems.
- Education
- BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.
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Role Summary
Senior Software Engineer role on the DGX Cloud team at NVIDIA, focused on scaling AI infrastructure that supports data science applications. The work centers on automating GPU infrastructure operations, reliability, and testing for large-scale distributed systems.
What You'll Do
- Contribute to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers
- Build end-to-end automation of data center management, break/fix, and system upkeep for large-scale Machine Learning systems
- Implement monitoring and health management capabilities for reliability, availability, and scalability of GPU assets
- Harness multiple data streams, from GPU hardware diagnostics to cluster and network telemetry
- Build automated test infrastructure used to qualify distributed systems for operation
- Partner with engineering teams across NVIDIA to integrate software from hardware up to AI training applications
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Senior engineer with 12+ years of large-scale production systems experience, a comparable degree or equivalent experience, and skills in systems programming, Linux, and Kubernetes or SLURM.
Required
- 12+ years of experience in a similar role working on large-scale production systems
- BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience
- Expert level knowledge of a systems programming language (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
Preferred
- 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 (Kubernetes, SLURM)
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Join a team of engineers at NVIDIA dedicated to scaling the AI infrastructure that powers cutting-edge data science applications. Our team solves complex challenges across datacenter hardware, networking, distributed systems, and software deployment. We collaborate closely to design and deliver leading infrastructure solutions. We value strong technical foundations paired with creative thinking and a bias toward execution. Together, we continuously push boundaries, grow our skills, and advance NVIDIA’s capacity to build and deploy AI-based infrastructure at scale.
What you will be doing:
- Contribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.
- Build end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems.
- Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets.
- Harness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
- Build automated test infrastructure that we use to qualify distributed systems for operation.
- Partner with engineering teams across NVIDIA to ensure the software integrates seamlessly from the hardware all the way up to the AI training applications.
What we need to see:
- 12+ years of experience in a similar role working on large-scale production systems.
- BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.
- Expert level knowledge of a systems programming language (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.
Ways to stand out from the crowd:
- 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 (Kubernetes, SLURM).
You will also be eligible for equity and benefits.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.