Solutions Architect - Financial Services

As a Solutions Architect at NVIDIA, you will work closely with industry sales, developer relationship managers, and product teams to bring NVIDIA's new technology into different industries. You will design the architecture of AI computing platforms, analyze AI and HPC applications, and deliver value to customers.

Responsibilities:

• 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 financial customers' workloads and demands for accelerated computing, including quant algorithms, portfolio optimization solving, trading algorithms, LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.
• Assist top financial customers in onboarding NVIDIA's software and hardware products and solutions, including CUDA, CUDA-X, and our libraries etc.
• Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Agentic AI, and other key applications.
• Be an internal champion for Data Analytics, Machine Learning, and Deep Learning among the NVIDIA technical community.

Requirements:

• 3+ years' experience with research/development/application of Machine Learning, data analytics, or HPC workflows.
• 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 for the financial field.
• Familiarity with financial technology stacks and common quant workflow 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.

Preferred Qualifications:

• Familiarity with algorithm trading pipeline, including data processing, prediction, portfolio optimization, and execution.
• LLM/Agent/Harness experience in the financial field.
• Engineering experience in areas such as model acceleration and kernel optimization.
• Extensive experience in designing and deploying large-scale HPC and enterprise computing systems.