Senior Solutions Architect

2 months ago

Bengaluru, Karnataka, India NVIDIA Full time

At NVIDIA, our mission is to collaborate with experts in addressing the world's most challenging problems in Large Language Models (LLM), Multi-modal Large Language Models (MLLM), Generative AI, and Retrieval-Augmented Generation (RAG) using our innovative platforms. A Senior Solution Architect at NVIDIA focuses on bringing technical expertise and innovative solutions to our partners and customers.

Key Responsibilities:

  • You will be part of our India Solution Architecture Team working with key Fortune 100 customers to drive NVIDIA technology adoption and secure innovative design wins in Data Center, Edge, and Cloud Deployments.
  • Develop and demonstrate solutions to customers based on NVIDIA's LLM, MLLM, and RAG application frameworks, LLM optimization, and scaled deployment frameworks.
  • Work closely with customers to build innovative blueprints for key Industry use-cases on LLM, MLLM, and RAG.
  • Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins for customers and growth of NVIDIA product features through customer feedback.

Requirements:

  • Bachelor's or Master's degree in Computer Science or equivalent experience.
  • Excellent understanding of NLP, LLM, MLLM, Generative AI, and RAG workflows.
  • 5+ years of experience as a Data Scientist with a proven track record in writing code in Python, PyTorch, or TensorFlow. C++ experience is a plus.
  • Ability to communicate ideas and code clearly through GitHub, documentation, and presentations.
  • Enjoy collaborating with teams across the organization, including Engineering, Research, Sales, Product, and Marketing.
  • Effective verbal and written communication, and technical presentation skills.
  • Self-starter with a passion for growth, enthusiasm for continuous learning, and sharing findings across the team.

What Sets You Apart:

  • External customer-facing skills and background.
  • Development experience with NVIDIA software platforms, libraries, and GPUs.
  • Knowledge of MLOps technologies such as Docker, containers, Kubernetes, and data center deployments.

We make extensive use of conferencing tools, but occasional travel is required for local on-site visits to customers and data science conferences. With highly competitive salaries, a comprehensive benefits package, and an excellent engineering work culture, NVIDIA is widely considered one of the technology industry's most desirable employers. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal-opportunity employer.

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