Senior AI Solutions Architect

6 days ago

Mumbai, Maharashtra, India NVIDIA Full time
Job Title: Senior Solutions Architect, Generative AI

NVIDIA is seeking a highly skilled and experienced Senior Solutions Architect to lead the development of cutting-edge generative AI solutions. As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering innovative solutions that leverage the power of NVIDIA's generative AI technologies.

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, stakeholders, and engineering teams to define product roadmaps and deliver AI software and hardware solutions.
  • Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions.
  • Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows.
  • 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.
Requirements:
  • 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.
Preferred Qualifications:
  • 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, memory efficiency, and 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.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. We value diversity in our current and future employees and do not discriminate 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.

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