Join NVIDIA as a Senior Solutions Architect specializing in Generative AI. This role focuses on architecting and delivering advanced solutions using NVIDIA's cutting-edge generative AI technologies, with a deep emphasis on Large Language Models (LLMs) and Agentic AI.

As a pivotal member of our AI Solutions team, you will architect and implement sophisticated solutions leveraging LLMs and Agentic AI, focusing on both training and deployment within the dynamic field of Generative AI.

Architect comprehensive generative AI solutions, emphasizing LLMs, Agentic workflows, and RAG (Retrieval-Augmented Generation).

Collaborate closely with clients to understand their unique language-based business challenges and craft bespoke solutions.

Support pre-sales efforts by preparing and delivering technical presentations, showcasing the capabilities of LLM and RAG technologies.

Engage directly with customers to thoroughly understand their language-related needs and challenges, leading workshops and design sessions.

Drive the training and optimization of Large Language Models using NVIDIA's powerful hardware and software platforms, and implement strategies for efficient LLM training to maximize performance.

Design and deploy RAG-based workflows to enhance content generation and information retrieval, integrating them seamlessly into customer applications and systems.

A strong foundation in Computer Science, Artificial Intelligence, or a related field, evidenced by a B.Tech, Master's, or Ph.D., or equivalent experience.

Possess at least 8 years of extensive hands-on experience in a technical capacity, with a significant focus on generative AI and training Large Language Models.

Demonstrate a proven history of successfully deploying and optimizing LLM models for production inference, alongside an in-depth understanding of state-of-the-art language models like GPT-3 and BERT.

Exhibit expertise in training and fine-tuning LLMs using prevalent frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.

Showcase proficiency in model deployment and optimization for efficient inference across diverse hardware, particularly GPUs, and a solid understanding of GPU cluster architecture for accelerated training and inference.

Excellent communication and collaboration skills are essential for articulating complex technical concepts to varied audiences and leading workshops effectively.