NVIDIA is hiring experienced Senior Production Engineers to help scale up its AI Infrastructure. We expect you to have significant experience with site reliability principles and techniques including reliability assessments, incident management processes, production system observability, monitoring and alerting, automated deployments and toil elimination. We view Production Engineering as a software engineering discipline and expect significant contributions to our codebase. 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 Production Engineering, 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 GPU asset provisioning, configuration, and lifecycle management across cloud providers.
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 Production Engineering/DevOps/SRE role within a highly technical organization with demonstrable impact from your work.
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.
8+ years in similar role and experience on large-scale production systems. Experience with the aforementioned Production Engineering/DevOps/SRE 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.
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.Skills Required
- 8+ years in a Production Engineering/DevOps/SRE role
- BS in Computer Science, Engineering, Physics, Mathematics
- Experience with GPU asset provisioning and lifecycle management
- Technical knowledge of systems programming language Go or Python
- Knowledge of cluster management systems like Kubernetes
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.”
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