# Technical Marketing Engineer  - AI Platform Software at NVIDIA

NVIDIA is hiring a Technical Marketing Engineer  - AI Platform Software in Santa Clara, United States. It pays $136k-$213k a year and Level rates it Builds AI ●●●●; you can [apply on NVIDIA](https://jobsbylevel.com/go/241fc8c1-8390-416e-85d8-1e86b8a8ee5f?utm_medium=ai-agent).

AI Level 4, AI centrality 83 out of 100. US, CA, Santa Clara.

## Details

- Company: [NVIDIA](https://jobsbylevel.com/companies/nvidia)
- AI level: AI Level 4 (score 83 out of 100)
- Location: US, CA, Santa Clara
- Salary: $136k-$213k
- Posted: July 30, 2026
- Apply: https://jobsbylevel.com/go/241fc8c1-8390-416e-85d8-1e86b8a8ee5f?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=technical-marketing-engineer-ai-platform-software-at-nvidia-7c23eb

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/technical-marketing-engineer-ai-platform-software-at-nvidia-7c23eb

## Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Are you a software developer, deep learning engineer, or scientist excited to collaborate with developers? NVIDIA is looking for a Technical Marketing Engineer (TME) to communicate the latest advancements in our AI Platform Software to the developer and user community. The AI Platform Software team manages the complete high-performance AI software stack: core kernel and communication libraries such as cuDNN and NCCL, open training platforms like PyTorch, and Megatron, and accelerated inference platforms such as TensorRT-LLM and Dynamo. This role works closely with product, engineering, and marketing teams to develop key technical content that guides developers how to use NVIDIA's AI platforms. Examples include technical blog posts, user guides, walk-throughs, demonstrations, benchmarks, and more. We seek a candidate who has trained a model, optimized an inference server, or debugged a multi-GPU job—and who is eager to share their expertise with others. You will review the stack before release and often be the first outside the engineering team to fully understand it. You'll be part of a collaborative group of TMEs, product managers, and developer advocates committed to delivering the best AI software platform for our developer community. What you'll be doing: Investigating new training and inference features while assessing them from a developer's point of view. Writing blog posts, guides, and reference examples that developers can use. Collaborating with internal and external deep learning engineers and researchers to build product-based training material and how-to technical content. Being the champion for AI among NVIDIA developers by directly engaging with our developer community. Improving product documentation to be clear for developers and their agents. Growing the value of our software by bringing community and customer feedback back to our product and engineering teams. Providing guidance to deep learning developers by building code samples and proof of concept applications. Benchmarking and generating data for positioning NVIDIA's inference platforms as the lowest cost-per-watt. What We Need to See: Bachelor's degree in Computer Science, Computer Engineering, or similar field or equivalent experience. 4+ years of practical experience in deep learning or machine learning, including research conducted during undergraduate and graduate studies. Hands-on experience with at least one training or inference framework such as PyTorch, JAX, Megatron, TensorRT-LLM, vLLM, SGLang, or comparable tools. Solid understanding of Python or C/C++, programming techniques, and software development. Something you have written or built for a technical audience that we can engage with: a blog post, tutorial, documentation set, conference talk, thesis chapter, or public repository. Passion for presenting to technical audiences and crafting content for developers. Prior success in balancing multiple projects at a time. Ways to Stand Out from the Crowd: Advanced knowledge of modern LLM and AI software architecture: attention kernels, parallelism strategies, quantization, KV cache management, and request scheduling. Sustained contributions to publicly accessible AI projects or developer forums. Experience running, tuning, or interpreting benchmarks on multi-GPU

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