NVIDIA’s Education Services team is dedicated to equipping partners with the expertise to support and fix the infrastructure software domain of NVIDIA AI Enterprise (NVAIE). This role focuses on empowering partners to master components such as Kubernetes, system virtualization, drivers, and management tools essential for deploying and maintaining accelerated AI systems. By designing and delivering hands-on training and support programs, you will help partners build the technical confidence needed to resolve infrastructure challenges independently. Your efforts will enable partners to ensure reliable, scalable, and efficient AI deployments, strengthening their ability to provide robust support across the NVAIE infrastructure ecosystem.
What you'll be doing:
Develop and deliver interactive training sessions on NVIDIA’s AI and MLOps platforms, focusing on software, support, and operational guidelines.
Create innovative training materials—including lab exercises, presentations and content aligned with evolving NVIDIA software and support offerings.
Collaborate with product and domain authorities to shape new support modules and joint training plans for enterprise customers and authorized learning partners (ALPs).
Support real-time solving, learner engagement, and technical guidance during workshops.
Work closely with lab manager and course developers to optimize training environments for software-specific labs.
What we need to see:
Bachelor’s degree in computer science, engineering, or related domain, or equivalent experience.
12+ years of professional experience, with a minimum of 2 years dedicated to AI software or MLOps environments.
Technical proficiency in: Linux, containerization (Kubernetes, Docker), orchestration tools, cloud environments
Hands-on experience with AI Tools, GPU Operator, ML frameworks (CUDA, RAPIDS, PyTorch, TensorFlow), and NVIDIA software stack.
Proven ability to communicate complex concepts to diverse audiences.
Strong English written and verbal communication skills.
Ways to Stand Out from the Crowd:
Direct experience developing training for AI software solutions.
Familiarity with NVIDIA AI Enterprise, Run:AI, BCM, and related MLOps tools.
Relevant technical certifications (Certified Kubernetes Administrator, RHCSA, NVIDIA Developer certifications, etc.).
Shown success in delivering high-quality, interactive workshops to technical audiences.
You will also be eligible for equity and benefits.
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.
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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.”
