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NVIDIA

Gen AI Product Evangelist Engineer, Supply Chain

Reposted 5 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Santa Clara, CA
160K-322K Annually
Senior level
In-Office or Remote
Hiring Remotely in Santa Clara, CA
160K-322K Annually
Senior level
The role involves creating technical content and demos for AI applications in Supply Chain, collaborating with engineers, and training developers.
The summary above was generated by AI

We are looking for a Product Evangelist Engineer to craft the fundamental technical content educating developers how to build multi-modal Gen AI applications using NVIDIA accelerated Computing platform. The role will primarily focus on building Gen AI demos, and AI Workflows for building the most efficient Gen AI use cases in Retail through video tutorials, technical blog posts, user guides, walk-throughs, and more. This material is essential in teaching developers about the latest advancements in NVIDIA Nemo platform, which includes multi-modal models, data curation, fine-tuning techniques, guardrails and inference optimization. Our Product Evangelist Engineers are drawn from best-in-class developers and scientists who enjoy working with the latest in GPU hardware and NVIDIA acceleration software! NVIDIA GPUs are used by the top Gen AI companies including Open AI, Mistral, Anthropic and Meta (Llama X).

This role will collaborate closely with our talented Retail Solution engineers who are working with customers and will develop demos of various use cases of Gen AI in Supply Chain. Our success has been based on laser-focused industry vertical business development, building a strong developer ecosystem and scaling out the business using a partner channel and creative marketing. We need a technical and creative individual to help us pursue more of these opportunities in Retail and CPG supply chain.

What you will be doing:

  • Develop customer facing multi-modal Generative AI demos specific to Supply Chain use cases and document the script, set-up environment for partners and solution architects to leverage.

  • Collaborate with internal and external LLM engineers and researchers to build product-based training material and how-to technical content and videos.

  • Develop workshops, Jupyter notebooks and AI Workflows to help developers build multi-modal Gen AI models for Supply Chain.

  • Document what you know and guide others. This can vary from building targeted training for partners, Solutions Architects and other internal stakeholders, to writing whitepapers, blogs, and to simply work through hard problems with a customer on a whiteboard.

  • Be the evangelist and champion for NVIDIA Accelerated Computing Platform and Nemo Microservices to Retail customers and developer community.

  • Collaborate with our engineering and development teams working on groundbreaking LLM technologies and drive our internal validation for our GPU accelerated Retail workflows.

  • Partner with our engineering and development teams working on groundbreaking LLM technologies and drive our internal validation for our GPU accelerated Retail workflows.

  • You will help with external community usability feedback to the internal teams to improve our product capabilities.  ​

What we need to see:

  • Bachelor’s degree in Computer Science, Computer Engineering, or similar field or equivalent experience.

  • 8+ years of meaningful work experience in software development, technical evangelism, technical marketing, or similar.

  • 3+ years of experience of deep domain expertise with LLM, deep learning and machine learning.

  • Strength presenting to technical audiences and generating content for developers.

  • Experience working with state of the art application deployment practices including but not limited to Docker/Containers and Kubernetes.

  • Experience with modern Deep Learning software architecture and frameworks. Embedded C/C++ and Python programming skills.

  • Strong written and demo development skills with the ability to effectively collaborate with management and engineering.

  • Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into complex projects.

  • A keen sense for product and innate ability to translate product value propositions to compelling demonstrations.

  • Strong analytical and problem-solving skills.

Ways to stand out from the crowd:

  • Full stack developer with front-end and back-end expertise.

  • Experience fine-tuning LLM models and RAG

  • Experience with CUDA programming and design practices using GPUs.

  • Background with NVIDIA GPUs and SDKs, especially with NVIDIA Nemo platform,

  • Published record of thought leadership in a technical area or industry segment published on Github or other platforms.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 160,000 USD - 253,000 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 8, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C/C++
Containers
Cuda
Deep Learning
Docker
Kubernetes
Machine Learning
Nvidia Accelerated Computing
Nvidia Nemo
Python

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