[Remote] Solutions Architect, Financial Services Capital Markets

Note: The job is a remote job and is open to candidates in USA. NVIDIA is a leading technology company seeking a Solutions Architect for Financial Services Capital Markets to join their experienced team. The role involves collaborating with engineering, product, and sales teams to drive success in deploying NVIDIA technology in the finance industry, focusing on high-performance computing and AI workloads.

Responsibilities

• 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

Skills

• 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 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
• 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

Benefits

• Equity
• Benefits

Company Overview

Company H1B Sponsorship