About the job
The Financial Services Solution Architect team is looking for an extraordinary person to join an experienced team of Quants and Data Scientists, engaging the finance industry with compelling examples of full-stack accelerated computing. Solution Architects work with top minds in Financial Services - Banking, Consumer Finance - to accelerate High-Performance Computing and AI workloads across various use cases. We’re seeking an inquisitive, hard-working, and creative individual passionate about helping tackle challenges. Join us in this endeavor!
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.
Qualifications
Minimum
BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields (or equivalent experience)
8+ 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
Preferred
Experience building and deploying Banking and Payments modeling techniques, such as: Time-series, Transformers, GraphNNs, XGBoost, Recommender Systems, etc
Familiarity with NLP Generative and Agentic AI models, frameworks, and applications
Skilled in deploying ML/DL models at scale on on-prem or public cloud computing clusters in production
Development experience with NVIDIA software libraries and GPUs
Knowledge of MLOps technologies such as Docker/containers, Kubernetes, data center deployments etc. Experience working with enterprise developers building AI, HPC, or data analytics applications