Senior AI Infrastructure Engineer - DGX Cloud
At a glance
Senior ML Platform & Ops role at NVIDIA. Remote, United States · full-time.
In listing ML Platform & Ops salary
remoteroles summary, based on the employer's posting.
What you'll do
- Build and operate internal tools for large AI training and inference platforms running on cloud infrastructure
- Test performance across large clusters with multiple GPUs and nodes, then analyze the results
- Guide services from initial design through release, day-to-day operation, and ongoing improvements
- Prepare services for launch with design advice, capacity planning, software tools, and launch reviews
- Monitor live service health and availability, automate scaling, improve reliability, and join production on-call
What you bring
- A computer science or related coding-focused degree, or equivalent practical experience
- At least five years of experience, including production infrastructure automation and distributed systems work
- Experience with cloud platforms, infrastructure as code, and Terraform
- Working knowledge of one or more of Python, Go, C/C++, or Java, plus Linux, networking, storage, or containers
Who this fits
This senior engineering role suits someone who can own infrastructure projects and collaborate across work initiated by others. You’ll support production systems through an on-call rotation. The position is remote within the United States.
From the employer
NVIDIA is looking for an outstanding, passionate, and dedicated Senior AI Infrastructure Engineer to join our DGX Cloud group. This engineering role will design, build and maintain large-scale production systems with high efficiency and availability using a combination of software and systems engineering practices. This role demands knowledge across different systems, networking, coding, databases, capacity management, continuous delivery and deployment, and open-source cloud-enabling technologies like Kubernetes and OpenStack.
The DGX Cloud Production Engineer at NVIDIA ensures our GPU cloud services deliver maximum reliability and uptime. They carefully prepare and plan changes to the system. They also manage capacity and performance. NVIDIA values diversity, curiosity, problem-solving, and openness. Our team includes people with varied backgrounds and perspectives. We encourage collaboration, big thinking, and risk-taking without blame. We promote self-direction on meaningful projects. We also provide support and mentorship to foster learning and growth.
What You’ll Be Doing:
Design, build, deploy, and run internal tooling for large-scale AI training and inferencing platform built on top of cloud infrastructure.
Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.
Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement.
Support services before they become available through activities such as system design consulting, developing software tools, platforms, and frameworks, capacity management, and launch reviews.
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.
Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity.
Practice sustainable incident response and blameless postmortems.
Be part of an on-call rotation to support production systems.
What We Need To See:
BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics), or equivalent experience.
5+ years of experience.
A track record showing a good balance between initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.
Background in infrastructure automation and distributed systems architecture focused on building tools to manage large-scale private or public cloud platforms in production.
Experience working with one or more of the following languages: Python, Go, C/C++, Java.
Comprehensive understanding in one or more of Linux, Networking, Storage, and Containers Technologies.
Experience with Public Cloud and Infrastructure as a Code (IAAC) and Terraform.
Distributed system experience.
Ways to Stand Out from the Crowd:
Interest in crafting, analyzing, and fixing large-scale distributed systems.
Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
Capability to identify issues and improve code performance while automating routine tasks. Experience in operating or handling large private and public cloud systems based on Kubernetes or Slurm.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. If you're creative and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: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 November 14, 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.