AI Innovation Leader

2 weeks ago

Mumbai, Maharashtra, India beBeeGenerative Full time US$ 1,50,000 - US$ 2,00,000

NVIDIA seeks a skilled Generative AI Architect to drive innovation in real-world deployments of cutting-edge technology.

Key Responsibilities
  • Design and implement end-to-end generative AI solutions with a focus on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) workflows.
  • Collaborate with customers to understand business needs and translate them into tailored LLM-based solutions.
  • Develop 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 high-performance computing 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 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 high-performance computing hardware and AI platforms.
Requirements
  • 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 high-performance computing hardware.
  • Experience presenting to clients and leading cross-functional collaboration.
  • Strong communication skills—able to clearly explain technical details to diverse audiences.
Preferred Qualifications
  • Experience deploying LLMs in cloud and on-prem clusters.
  • Proficiency with Docker, Kubernetes, and high-performance computing cluster management.
  • Proven ability to optimize LLM inference for speed, memory, and cost.
  • Hands-on experience with high-performance computing hardware, profiling, and distributed model execution.

Join us in shaping the future of AI and contributing to the development of large-scale LLM solutions.

We are committed to diversity in our workforce.

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