Solution Architect - AI Labs

NVIDIA are seeking Solution Architects with specialized expertise in training and deploying Large Language Models (LLMs), implementing RAG workflows, and agentic inference.

You will leverage the full NVIDIA software & hardware ecosystem to design, optimize, and deliver production-grade generative AI solutions for enterprise customers.

What You'll Be Doing:

• Conduct in-depth analysis of customers' latest needs and co-develop accelerated computing solutions with key customers.
• Assist in supporting industry accounts and driving research/influencing/new business in those accounts.
• Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
• Understand and analyze Top AI Labs customers' workloads and demands for accelerated computing, including but not limited to: LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.
• Assist Top AI Laps customers in onboarding NVIDIA's software and hardware products and solutions, including but not limited to: CUDA, TensorRT-LLM, NeMo Framework, etc.
• Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
• Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.

What We Need To See:

• 3+ years’ experience with research/development/application of Machine Learning, data analytics, or computer vision work flows.
• Outstanding verbal and written communication skills. Ability to work independently with minimal day-to-day direction.
• Knowledge of industry application hotspots and trends in AI and large models.
• Familiarity with large model-related technology stacks and common inference/training optimization methods. C/C++/Python programming experience.
• Desire to be involved in multiple diverse and innovative projects.
• Experience using scale-out cloud and/or HPC architectures for parallel programming.
• MS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or equivalent experience.

Ways To Stand Out From The Crowd:

• AIGC/LLM/NLP experience.
• CUDA optimization experience.
• Experience with Deep Learning frameworks and tools.
• Engineering experience in areas such as model acceleration and kernel optimization.
• Extensive experience designing and deploying large scale HPC and enterprise computing systems.