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.