Senior Solutions Architect, Generative AI

NVIDIA; Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

NVIDIA is seeking a dynamic Generative AI Solution Architect to design LLM and RAG-based workflows. You will partner with customers to translate language-related challenges into scalable solutions and collaborate with sales to showcase capabilities.

You will guide workshops and training, embedding NVIDIA hardware/software for optimal LLM performance. Required are advanced degrees and 5+ years in generative AI, with strong PyTorch/TensorFlow and Transformers expertise, plus cloud/on-prem

Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent.
• 5+ years in a technical role with emphasis on generative AI and LLMs.
• Proven deployment and optimization of LLMs in production.

Responsibilities

• Architect end-to-end generative AI solutions with LLMs and RAG workflows.
• Collaborate with customers to understand language challenges and tailor solutions.
• Support pre-sales with technical demos of LLM and RAG capabilities.
• Work with NVIDIA engineers to influence generative AI technology evolution.
• Lead workshops to define and refine LLM/RAG-based solutions and training.

Skills

LLM training

RAG workflows

TensorFlow/PyTorch

Hugging Face Transformers

GPU clusters

Communication

Workshops/Training

Cloud/on-prem deployment

Education

Master's or Ph.D. in CS/AI

Tools

Docker

Kubernetes

NVIDIA CUDA

Cloud platforms (AWS/Azure/GCP)

Job description

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with specialized expertise in training Large Language Models (LLMs) and implementing workflows based on Retrieval-Augmented Generation (RAG). As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering cutting-edge solutions that leverage the power of NVIDIA's generative AI technologies. This position requires a deep understanding of language models, particularly LLMs, and a strong proficiency in designing and implementing RAG-based workflows.

What you will be doing:

• Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows.

• Collaborate closely with customers to understand their language-related business challenges and design tailored solutions.

• Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of LLM and RAG capabilities.

• Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI technologies.

• Engage directly with customers to understand their language-related requirements and challenges.

• Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows and lead the training and optimization of Large Language Models using NVIDIA’s hardware and software platforms.

• Implement strategies for efficient and effective training of LLMs to achieve optimal performance.

• Design and implement RAG-based workflows to enhance content generation and information retrieval.

• Work closely with customers to integrate RAG workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies.

• Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions.

What we need to see:

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience

• 5+ years of hands-on experience in a technical role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs).

• Proven track record of successfully deploying and optimizing LLM models for inference in production environments.

• In-depth understanding of state-of-the-art language models, including but not limited to GPT-3, BERT, or similar architectures.

• Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.

• Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs.

• Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference.

• Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

• Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences.

Ways to stand out from the crowd:

• Experience in deploying LLM models in cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.

• Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization.

• Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.

• Deep understanding of GPU cluster architecture, parallel computing, and distributed computing concepts.

• Hands-on experience with NVIDIA GPU technologies, and GPU cluster management and ability to design and implement scalable and efficient workflows for LLM training and inference on GPU clusters

With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! 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.