Nvidia Senior Solutions Architect Financial Services Capital Markets 

United States, Texas 

897264918

What You’ll Be Doing:

• Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins at customers. Enable development and growth of NVIDIA product features through customer feedback and proof-of-concept evaluations.

• Perform proof-of-concepts working side by side with clients, engineers, and other architects on in-depth analysis, profiling and optimization of machine learning/deep learning models to ensure the best performance on current- and next-generation GPU architectures.

• Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and issues to drive success using NVIDIA technology.

• Facilitate rapid resolution of customer issues and promote the highest levels of customer satisfaction.

• Build collateral (notebooks/ blogs) applied to Finance industry use-cases such as ML/DL, recommender systems, GNN, monte-carlo simulations, Quantitative Finance, etc. by working closely with customers.

What We Need To See:

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields (or equivalent experience)

• 12+ years experience as an ML/Software Engineer with a proven track record in writing code in Python, C++

• Experience with ML/DL algorithms with frameworks such as PyTorch, Spark, Dask, Jax, TensorFlow

• Ability to communicate ideas and share code clearly through blog posts, GitHub

• Enjoy working with multiple levels and teams across organizations(engineering/research,product, sales, and marketing teams)

• Effective verbal/written communication and technical presentation skills

• Self-starter with a passion for growth, a real enthusiasm for continuous learning, and sharing findings across the team

• Skilled in deploying ML/DL models at scale on public cloud computing and/or on-prem HPC clusters in production

Ways To Stand Out From The Crowd:

• Demonstrate C/C++ programming proficiency with an understanding of software design, programming techniques, and algorithms, alongside experience performing performance optimizations.

• Familiarity with NVIDIA GPU architectures.

• GPU Development experience through NVIDIA CUDA-x libraries, cuBLAS, cuDNN.

• Knowledge of MLOps technologies such as containers, data center deployments, cluster management software, etc.

• Experience working with enterprise developers building HPC or data analytics applications.