Product Marketing MBA Intern, AI Infrastructure
NVIDIA
This job at a glance
- Who can apply
- New grads and up to 1 year · MBA / PGDM
- Must know
- MarketingNetworkingContent writingProduct managementMachine learningDeep learning
- Work
- On-site in Santa Clara · internship
- Pay
- Not stated by the employer.
- Skill demand
- Marketing75%Product management62%Content writing11%Networking9%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 3, 2026 · still open
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About the Role
NVIDIA is looking for a Product Marketing MBA Intern to join the team driving awareness and thought leadership for NVIDIA’s AI infrastructure platform. This role is focused on telling the story of NVIDIA's AI infrastructure and inference leadership to a broad audience. The work involves translating technical material into actionable narratives for customers, partners, and analysts.
Key Responsibilities
- Work with engineering, product, and solution architecture teams to understand the technical capabilities of NVIDIA’s AI infrastructure and inference stack, including accelerated compute, networking, CUDA libraries, model architectures, and deployment techniques.
- Research and synthesize developments in inference, such as model architectures, serving frameworks, optimization techniques, arXiv, and industry papers, and identify intersections with NVIDIA’s platform to maximize performance and minimize cost.
- Author core content that builds awareness and thought leadership: blog posts, technical explainers, presentations, briefing materials, and narrative frameworks.
- Partner with PR, campaigns, analyst relations, and developer marketing teams to carry content across channels and maximize reach.
- Own a defined summer project end to end, from research through to a published or presented deliverable.
Requirements & Tech Stack
- Currently pursuing an MBA degree (December 2027 to summer 2028 graduation date) with a previous Bachelor’s in a technical field such as engineering, computer science, or another STEM discipline.
- Prior full-time experience in an engineering, product management, or technical product role.
- Working understanding of AI/ML fundamentals, including how models are trained and served, and what makes inference hard at scale.
- Excellent written and verbal communication, with ability to translate complex technical concepts for non-specialist audiences.
- Ability to work independently with directional feedback, and a bias toward moving quickly.
Ways To Stand Out
- Familiarity with modern data center and accelerated computing concepts.
- Familiarity with deep learning frameworks (PyTorch, JAX).
- Familiarity with inference serving and optimization approaches (TensorRT-LLM, vLLM, SGLang, Triton Inference Server, or similar).
- Published technical writing, blog posts, or conference talks explaining AI systems, infrastructure, or inference.
- Experience with hyperscale cloud providers or large-scale AI infrastructure.