9 days ago

Senior Generative AI Solutions Architect

NVIDIA

On Site
Full Time
$200,000
Mumbai, Maharashtra, India

Job Overview

Job TitleSenior Generative AI Solutions Architect
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$200,000
LocationMumbai, Maharashtra, India

Who's the hiring manager?

Sign up to PitchMeAI to discover the hiring manager's details for this job. We will also write them an intro email for you.

Uncover Hiring Manager

Job Description

Senior Generative AI Solutions Architect at NVIDIA

NVIDIA is seeking a dynamic and experienced Senior Generative AI Solutions 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.
  • 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.
  • 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.
  • 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.

Key skills/competency

  • Generative AI
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Deep Learning Frameworks (TensorFlow, PyTorch)
  • GPU Optimization
  • Cloud Deployment (AWS, Azure, GCP)
  • Containerization (Docker, Kubernetes)
  • Solution Architecture
  • Technical Leadership
  • Customer Engagement

Tags:

Senior Generative AI Solutions Architect
LLM training
RAG workflows
solution architecture
customer collaboration
technical leadership
model deployment
optimization
pre-sales support
workshop facilitation
staying current
GPT-3
BERT
TensorFlow
PyTorch
Hugging Face
GPUs
CUDA
Docker
Kubernetes
AWS
Azure
GCP

Share Job:

How to Get Hired at NVIDIA

  • Research NVIDIA's AI Vision: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor, focusing on their Generative AI leadership.
  • Tailor your resume for Generative AI: Customize your resume to highlight experience in LLM training, RAG workflows, deep learning projects, and GPU optimization relevant to NVIDIA.
  • Showcase practical LLM/RAG projects: Prepare to discuss successful deployments, optimizations, and technical challenges overcome in Generative AI initiatives.
  • Master NVIDIA's ecosystem: Demonstrate strong familiarity with NVIDIA GPUs, CUDA, AI platforms, and distributed computing concepts in interviews.
  • Articulate your problem-solving approach: Practice explaining how you would architect, implement, and optimize solutions for complex customer Generative AI challenges.

Frequently Asked Questions

Find answers to common questions about this job opportunity

Explore similar opportunities that match your background