Solutions Architect, Financial Services Banking

at Nvidia
📍 New York City, United States
USD 224,000-356,500 per year
MIDDLE
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Marketing @ 3 Docker @ 2 Kubernetes @ 2 Python @ 7 Spark @ 3 GitHub @ 6 Algorithms @ 3 Machine Learning @ 3 MLOps @ 2 TensorFlow @ 3 Mathematics @ 3 NLP @ 2 PyTorch @ 3 XGBoost @ 3 GPU @ 3

Details

The Financial Services Solution Architect team is looking for an extraordinary person to join an experienced team of quants and data scientists to engage the finance industry with full-stack accelerated computing. You will help accelerate High-Performance Computing (HPC) and AI workloads across Financial Services use cases (Banking, Consumer Finance) and work directly with customers to design, prototype, and optimize production ML/DL workflows on GPU-accelerated platforms.

Responsibilities

  • Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins and enable product feature growth through customer feedback and proof-of-concept evaluations.
  • Perform proof-of-concepts with clients, engineers, and other architects, including in-depth analysis, profiling, and optimization of machine learning and deep learning models for best performance on current- and next-generation GPU architectures.
  • Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and production issues to drive success using NVIDIA technology.
  • Facilitate rapid resolution of customer issues and promote high levels of customer satisfaction.
  • Build collateral (notebooks, blog posts, sample code) applied to Finance industry use cases such as ML/DL, recommender systems, GNNs, Monte Carlo simulations, and quantitative finance methods.
  • Share findings and best practices across internal and customer teams; present technical content clearly to multiple audiences.

Requirements

  • BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other engineering fields — or equivalent experience.
  • 12+ years of experience as an ML/Software Engineer with proven production coding experience in Python and C++.
  • Experience with ML/DL algorithms and frameworks such as TensorFlow, Jax, PyTorch, Spark, and Dask.
  • Experience profiling and optimizing models for GPU architectures and familiarity with NVIDIA software libraries and GPUs.
  • Hands-on experience or strong understanding of deploying ML/DL models at scale on on-premise or public cloud clusters in production.
  • Familiarity with MLOps technologies and containers (Docker), orchestration (Kubernetes), and data center deployments.
  • Ability to communicate ideas and share code clearly (blogs, notebooks, GitHub) and strong verbal/written presentation skills.
  • Self-starter mentality with passion for continuous learning and collaboration across engineering, research, product, sales, and marketing teams.

Ways To Stand Out

  • Experience building and deploying Banking and Payments models: time-series modeling, Transformers, Graph Neural Networks, XGBoost, and recommender systems.
  • Familiarity with NLP generative and agentic AI models, frameworks, and applications.
  • Deep experience deploying ML/DL models at scale in production (cloud and on-prem) and working with enterprise developers on AI, HPC, or data analytics applications.
  • Prior development experience working with NVIDIA software libraries and GPU-accelerated stacks.

Compensation & Benefits

  • Base salary range: 224,000 USD - 356,500 USD (final base determined by location, experience, and comparable employees).
  • Eligible for equity and company benefits (see NVIDIA benefits).

Additional Information

  • Location: New York (United States).
  • Employment type: Full time.
  • Applications accepted at least until September 1, 2025.
  • NVIDIA is an equal opportunity employer committed to a diverse work environment.