Join NVIDIA's Solution Architect team as a Senior Solution Architect, focusing on Generative AI. This role involves working with cutting-edge computing hardware and software to drive breakthroughs in artificial intelligence, particularly in Large Language Models (LLMs) and agentic AI. You will collaborate with technology partners and customers to integrate NVIDIA solutions, fostering innovation and enabling end-user success in a fast-paced, evolving field. We seek individuals passionate about AI who can maintain strong collaborations across marketing, business development, and engineering teams, shaping the future of human-technology interaction.

This position offers the opportunity to work with the latest AI architectures and advanced neural network models. You will be instrumental in developing and deploying solutions that redefine how people engage with technology.

Architect comprehensive end-to-end generative AI solutions, with a strong focus on LLM training, deployment, and Retrieval Augmented Generation (RAG) workflows. Engage closely with customers to grasp their language-related business challenges and engineer bespoke solutions.

Collaborate with NVIDIA engineering teams, providing crucial feedback to advance generative AI software. Lead workshops and design sessions to meticulously define and refine generative AI solutions, specializing in LLMs and RAG. Conduct training and optimization of Large Language Models using NVIDIA's robust hardware and software platforms, implementing strategies for efficient and effective LLM training to achieve peak performance.

Provide technical leadership and expert guidance on best practices for LLM training and the implementation of RAG-based solutions. Directly interact with customers and partners to thoroughly understand their requirements and overcome challenges.

Possess a Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience. You should have over 7 years of hands-on experience in a technical AI role, with a specific concentration on generative AI and extensive experience training Large Language Models (LLMs).

Demonstrate a proven history of successfully deploying and optimizing LLM models for inference within production environments. Exhibit expertise in training and fine-tuning LLMs using leading frameworks like Megatron-LM, Megatron-Bridge, AutoModel, and PyTorch. Be proficient in model deployment and optimization techniques for efficient inference on diverse hardware, especially GPUs.

Showcase strong knowledge of GPU cluster architecture and the capability to leverage parallel processing for accelerated model training and inference. Possess excellent communication and collaboration skills, enabling you to articulate complex technical concepts to both technical and non-technical audiences. Experience leading workshops, training sessions, and presenting technical solutions to varied groups is essential.