Nvidia Solutions Architect Financial Services 

United States, Texas 

109206717

What You’ll Be Doing:

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

• Work directly with client Data Scientists and developers on business-impacting workflows, projects, issues and success using NVIDIA technology.

• Build collateral (notebook/ blog) applied to Finance industry use-cases such as Generative AI, recommender, GAN, GNN, monte-carlo, Quantitative Finance, etc. by working closely with customers.

• Collaborate with key industry partners/customer developers to build GPU-accelerated solutions that are applied to their products and technologies.

• Partner with NVIDIA Engineering, Product Engineering, 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.

What We Need To See:

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

• 5+ 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 TensorFlow, Jax, PyTorch, Spark, Dask

• 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

Ways To Stand Out From The Crowd:

• Skilled in deploying ML/DL models at scale on public cloud computing clusters in production

• Development experience with NVIDIA software libraries and GPUs

• Knowledge of MLOps technologies such as Docker/containers, Kubernetes, KubeFlow, data center deployments etc. Experience working with enterprise developers building AI, HPC, or data analytics applications