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AI Job Summary

You'll work on production systems for GPU clusters running AI workloads, focusing on Kubernetes resource scheduling, GPU health monitoring, and cluster reliability. The role requires 5+ years of software engineering experience with Kubernetes APIs, systems programming languages like Go or Python, and expertise managing large-scale distributed systems. Strong communication and ability to coordinate across teams is essential. Base salary ranges from $152,000–$241,500 (Level 3) to $184,000–$287,500 (Level 4), plus equity and benefits.

Written from this posting by Neural Jobs AI. The full description is below.

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Job Description

NVIDIA is hiring experienced software engineers with kubernetes experience to help scale up its AI Infrastructure. We expect you to have significant software engineering experience with kubernetes including cluster operations, operator development, node health monitoring and working with GPU resource scheduling. We welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications. If you're creative, passionate about kubernetes and GPUs, and love having fun, please apply today!
 

For two decades, we have pioneered visual computing, the art and science of computer graphics. With the invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning.


What you will be doing:

  • You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. This includes working on custom software related to scheduling GPU resources on kubernetes.
  • Implementing monitoring and health management capabilities that enable industry leading reliability, availability, and scalability of GPU assets. You will be harnessing multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
  • Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance.  Evaluating system failures and improving services based on a well-defined incident management process. 

What we need to see:

  • Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work.  Software development experience with kubernetes APIs and frameworks not just operating a cluster.
  • Highly motivated with strong communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies.
  • 5+ years in similar role and experience on large-scale production systems.  Experience with common software engineering principles, tools and techniques. 
  • You possess a BS in Computer Science, Engineering, Physics, Mathematics or a comparable Degree or equivalent experience.
  • Technical knowledge, including a systems programming language (Go, Python) and a solid understanding of data structures and algorithms.  

Ways to stand out from the crowd:

  • Technical competency in managing and automating large-scale distributed systems independent of cloud providers. Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, Slurm, Bright Cluster Manager)
  • Proven operational excellence in maintaining reliable and performant AI infrastructure.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 2, 2026.

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.

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  • Role Senior Software Engineer, Distributed Systems Engineer - DGX Cloud
  • Experience 5-7 years
  • Education Bachelor Degree, or equivalent experience
  • Work type Remote
  • Location United States
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NVIDIA
Hardware & Semiconductors · 200-500 Members · Santa Clara, CA, United States

NVIDIA builds the GPUs and the CUDA software stack that most modern AI is trained and served on, along with its own research in graphics, robotics and foundation models.

All jobs at NVIDIA
Job Overview

Approx. salary range

189K – 298K

Our estimate — this employer did not publish a salary

Our estimate, not the employer’s. Worked out from the middle half of 64 comparable roles on Neural Jobs that did publish a salary, in the same field, country and experience band. The real figure for this job may be different.

Eligibility
United States Hires remotely in the United States.
Workplace
Remote
Job Posted:
1 day ago
Job Type
Full Time
Education
Bachelor Degree, or equivalent experience
Experience
5-7 years

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