United States onlyNVIDIA is seeking outstanding Solutions Architect to help grow our OEM enterprise AI business. At NVIDIA, our solutions architects work across different teams and enjoy helping partners and customers with the latest Accelerated Computing and Generative AI, and AI Factory deployments. We're looking to grow our company and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our OEM partners and work on exciting software solutions focused on enabling enterprise Generative AI workflows. You should be comfortable working in a multifaceted environment and have experience with Generative AI, LLMs, Deep Learning, and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team using the latest technologies at NVIDIA!
What You Will Be Doing:
Working with our OEM partners to architect enterprise-grade end-to-end generative AI SW solutions.
Collaborate closely with OEM partners' SW development teams to help craft world-class joint AI solutions.
Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of Generative AI capabilities.
Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI software.
Engage directly with customers/partners to understand their requirements and challenges.
Lead workshops and design sessions to define and refine generative AI solutions with a strong emphasis on enterprise workflows.
Implement strategies for efficient and effective training of LLMs to achieve peak performance.
Design and implement RAG-based workflows to improve content generation and information retrieval.
What We Need To See:
3-5+ years of hands-on experience as a solution architect or similar with a specific focus on AI solutions.
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
Proven track record of successfully deploying and optimizing Generative AI models for inference in production environments.
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.
Solid understanding of GPU cluster architecture and the ability to bring to bear 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 collaborators.
Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences.
Ways To Stand Out From The Crowd:
Experience in deploying Generative AI models in cloud environments and on-premises infrastructures.
Experience with NVIDIA GPUs and software libraries, such as NVIDIA NIM, NVIDIA NeMo Framework, NVIDIA Triton Inference Server, TensorRT, TensorRT-LLM.
Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization.
Familiarity with Docker or equivalent experience in containerization technologies and Kubernetes for scalable and efficient model deployment.
Deep understanding of GPU cluster architecture, parallel computing, and distributed computing concepts.
You will also be eligible for equity and benefits.
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