Technical Product Marketing MBA Intern
NVIDIA
This job at a glance
- Who can apply
- 25–27 years of experience · MBA / PGDM
- Must know
- MarketingSalesContent writingProduct managementLLMsMarket research
- Work
- On-site in Santa Clara · internship
- Pay
- Not stated by the employer.
- Skill demand
- Marketing73%Sales67%Product management59%Content writing6%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 4, 2026 · still open
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About the Role
NVIDIA is seeking an MBA Intern to join the AI Infrastructure product marketing team. You will collaborate with product, marketing, and sales teams to translate accelerated computing technologies into clear messaging, compelling content, and business value for customers.
Key Responsibilities
- Researching customer needs, market trends, and competitive offerings across AI infrastructure, training, inference, and accelerated computing.
- Developing messaging and positioning that connect technical capabilities to customer priorities, including performance, energy efficiency, deployment simplicity, and total cost of ownership.
- Building marketing content, such as customer stories, presentations, solution briefs, blogs, and sales enablement materials.
- Working with technical teams to interpret performance data and turn findings into evidence-based value propositions for technical and business audiences.
- Delivering an internship project with clear objectives, achievements, and outcomes, and presenting recommendations to collaborators across product management, engineering, sales, and marketing.
Requirements & Tech Stack
- Pursuing an MBA or a related field, or possessing equivalent experience (graduating in winter 2027 or summer 2028).
- BS or MS in engineering, computer science, or a related technical field, or equivalent experience.
- Working knowledge of AI and cloud or data center computing, including AI training and inference.
- Experience producing customer-facing content such as product collateral, web copy, or briefs.
- Experience analyzing data to support recommendations.
- Hands-on experience with AI assistants and agentic workflows to accelerate day-to-day work.
Qualifications (Ways to Stand Out)
- Background in product marketing, product management, engineering, technical consulting, or enterprise technology.
- Experience with generative AI, AI agents, inference, accelerated computing, or cloud infrastructure.
- Translating technical capabilities into customer benefits, economic analysis, or differentiated positioning.
- Contributions to product launches, customer case studies, market research, or sales enablement.
- Examples of independent ownership, project management, and collaboration across technical and business teams.