Technical Marketing Engineer - AI Platform Software

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Technical Marketing Engineer to communicate advancements in their AI Platform Software to the developer community. This role involves investigating new training and inference features, creating technical content (blog posts, guides, demos), and providing guidance to deep learning developers. The candidate will also gather community feedback and benchmark inference platforms.

What you'd actually do

  1. 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.
  2. Collaborating with internal and external deep learning engineers and researchers to build product-based training material and how-to technical content.
  3. Being the champion for AI among NVIDIA developers by directly engaging with our developer community.
  4. Improving product documentation to be clear for developers and their agents.
  5. Growing the value of our software by bringing community and customer feedback back to our product and engineering teams.

Skills

Required

  • 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.

Nice to have

  • 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 systems.
  • Experience explaining a system you did not build to people who need to use it tomorrow.

What the JD emphasized

  • trained a model
  • optimized an inference server
  • debugged a multi-GPU job
  • Hands-on experience with at least one training or inference framework
  • Something you have written or built for a technical audience that we can engage with

Other signals

  • Technical Marketing Engineer
  • AI Platform Software
  • developer community
  • training and inference features
  • TensorRT-LLM