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. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.
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.