Senior Solutions Architect, Financial Services Banking

NVIDIA NVIDIA · Semiconductors · NY +2 · Remote

Senior Solutions Architect for Financial Services Banking at NVIDIA, focusing on accelerating High-Performance Computing and AI workloads. The role involves partnering with engineering, product, and sales teams, performing proof-of-concepts, optimizing ML/DL models on GPU architectures, and building collateral for finance industry use cases. Requires deep experience in ML/DL algorithms, frameworks, and deploying models at scale.

What you'd actually do

  1. 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.
  2. 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.
  3. Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and issues to drive success using NVIDIA technology.
  4. Facilitate rapid resolution of customer issues and promote the highest levels of customer satisfaction.
  5. 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

Required

  • 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
  • Python
  • C++
  • TensorFlow
  • Jax
  • PyTorch
  • Spark
  • Dask
  • communicating ideas and sharing code clearly through blog posts, GitHub
  • working with multiple levels and teams across organizations
  • 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

Nice to have

  • 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

What the JD emphasized

  • proven track record
  • ML/DL algorithms
  • deploying ML/DL models at scale

Other signals

  • customer-facing
  • performance optimization
  • GPU architectures
  • ML/DL algorithms
  • deploying ML/DL models at scale