Joining NVIDIA's DGX Cloud Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI and Data infrastructure tools and services. 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 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 AI, LLM, and GenAI infrastructure.
Develop and optimize tools to improve infrastructure efficiency and resiliency.
Root cause and analyze and triage failures from the application level to the hardware level
Enhance infrastructure and products underpinning NVIDIA's AI platforms.
Co-design and implement APIs for integration with NVIDIA's resiliency stacks.
Define meaningful and actionable reliability metrics to track and improve system and service reliability.
Skilled in problem-solving, root cause analysis, and optimization.
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.
Proven track record in building and scaling large-scale distributed systems.
Experience with AI training and inferencing and data infrastructure services.
Familiar in operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).
Proficiency in programming languages such as Python, C/C++, script languages
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:
Experience in working with the large scale AI cluster
Strong understanding of NVIDIA GPUs, network technologies (RDMA, IB, NCCL)
Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, and Ray
Experience and root cause analysis of failures and datacenter scale
Strong background in software design and development.
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.
Skills Required
- 8+ years of experience in developing software infrastructure for large-scale AI systems
- Bachelor's degree in Computer Science or related field
- Strong debugging skills and experience in analyzing AI applications
- Experience with AI training, inferencing, and data infrastructure services
- Proficiency in programming languages such as Python and C/C++
- Experience with observability platforms for monitoring (e.g., ELK, Prometheus)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
