Senior Solutions Architect, Generative AI

5 - 8 years

5 - 8 Lacs

Posted:2 days ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology.

What You Will Be Doing

  • Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows.
  • Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions.
  • Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems.
  • Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency.
  • Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications.
  • Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies.
  • Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms.

What We Need To See

  • Master's or Ph.D. in Computer Science, AI, or a related field
  • 5+ years of hands-on experience with LLM training, deployment, and production optimization
  • Deep understanding of language models like GPT-3, BERT, and experience with RAG
  • Proficient in PyTorch, TensorFlow, and Hugging Face Transformers
  • Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware
  • Experience presenting to clients and leading cross-functional collaboration
  • Strong communication skillsable to clearly explain technical details to diverse audiences

Ways To Stand Out From The Crowd

  • Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters
  • Proficiency with Docker, Kubernetes, and GPU cluster management
  • Proven ability to optimize LLM inference for speed, memory, and cost
  • Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution

If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next.

We are an equal opportunity employer and committed to diversity in our workforce.

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