Senior DGX Cloud AI Infrastructure Software Engineer

NVIDIA is hiring a Senior DGX Cloud AI Infrastructure Software Engineer in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
The listed pay starts 10% above the typical software engineer posting on Level.
Tools and skills the posting cites include PyTorch, TensorFlow and JAX.
Level classifies it as a senior role.
Level lists 2,600+ other open roles at NVIDIA.

AI in this role

Design, build, and maintain large-scale AI infrastructure software to optimize efficiency and resiliency for AI workloads.

PyTorchTensorFlowJAXKubernetesPrometheusElkLoki

ai-researchdistributed-systemsinfrastructuredebuggingperformance-optimization

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on developing tools for optimizing efficiency and resiliency of AI workloads - pre-training, post-training, inference. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. We are seeking an AI infrastructure software engineer to join our team. You'll be instrumental in designing, building, and maintaining AI infrastructure that enable large-scale AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of AI systems.

As a senior DGX Cloud AI Infrastructure software engineer at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science and be part of a dynamic, diverse, and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now!

What you’ll be doing:

Develop infrastructure software and tools for large-scale pre-training, post-training, and inference.
Develop and optimize tools and libraries to improve infrastructure efficiency and resiliency.
Co-design and implement APIs for integration with NVIDIA's resiliency stacks.
Enhance infrastructure and products underpinning NVIDIA's AI platforms.
Define meaningful and actionable reliability metrics to track and improve system and service reliability.
Skilled in problem-solving, root cause analysis, and optimization.
Root cause and analyze and triage failures from the application level to the hardware level

What we need to see:

Minimum of 8+ years of experience in developing software infrastructure for large scale AI systems.
Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience).
Strong debugging skills and experience in analyzing and triaging AI applications from the application level to the hardware level.
Experience with observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).
Proven track record in building and scaling large-scale distributed systems.
Experience with AI training and inferencing infrastructure services.
Proficiency in programming languages such as Python, C/C++, script languages
Experience in quality software engineering practices, including test development, defensive programming, version control, and CI.
Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Ways to stand out from the crowd:

Background in working with the large scale clusters
Experience in defining and building observability and telemetry software stack
Experience with RDMA software stack (NCCL, IB verbs, ucx, libfabrics)
Experience and root cause analysis of failures and datacenter scale
Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, and Ray

NVIDIA leads 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

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:
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 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.

How we rate this

Senior DGX Cloud AI Infrastructure Software Engineer at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior DGX Cloud AI Infrastructure Software Engineer is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on September 29, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchDistributed SystemsInfrastructureDebuggingPerformance OptimizationPyTorchTensorFlowJAX

Also common in software engineer jobs at this level

LLM Machine learning AWS AI agents Kubernetes Generative AI

Pay

This job starts at: $184k
Typical software engineer job: $167k

This posting starts 10% above the typical software engineer job. See software engineer jobs

Questions you could be asked

Tell me about a research question you investigated. What did you find?
Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Tell me about a project where debugging was part of your work. What did you do?
Tell me about a project where performance optimization was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Research, Distributed Systems, Infrastructure, Debugging, and Performance Optimization. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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