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Nvidia Solutions Architect Financial Services 
United States, Texas 
772808452

24.06.2024

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

You will also be eligible for equity and .