Solutions Architect - Financial Services

Designs and validates accelerated computing architectures for financial services customers, analyzing their workloads (quant algorithms, LLM inference, portfolio optimization) and guiding adoption of NVIDIA hardware and software. Works with sales and product teams to deliver technical demos, proof-of-concepts, and onboarding support. Differs from typical SA roles by requiring deep domain knowledge of financial workflows and algorithm optimization rather than broad platform expertise.

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. You will work closely with industry sales, developer relationship managers and product teams in the hiring position. 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 financial customers' workloads and demands for accelerated computing, including but not limited to: 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 but not limited to: 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. What We Need To See: 3+ years’ experience with research/development/application of Machine Learning, data analytics, or HPC 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 for 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. Ways To Stand Out From The Crowd: Be familiar with algorithm trading pipeline, including data processing, prediction, portfolio optimization, and execution. LLM/Agent/Harness experience in financial field experience Engineering experience in areas such as model acceleration and kernel optimization. Extensive experience in designing and deploying large scale HPC and enterprise computing systems.