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 with Financial Services Capital Markets and Exchange firms 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 solve challenges. Join us in this endeavor!
What You’ll Be Doing:
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.
What We Need To See:
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
Ways To Stand Out From The Crowd:
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.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering field (or equivalent experience)
- 5+ years experience as an ML/Software Engineer with proven track record writing code in Python and C++
- Experience with ML/DL algorithms and frameworks such as PyTorch, Spark, Dask, Jax, TensorFlow
- Ability to communicate ideas and share code clearly through blog posts and GitHub
- Experience working cross-functionally with engineering/research, product, sales, and marketing teams
- Effective verbal/written communication and technical presentation skills
- Self-starter with passion for continuous learning and sharing findings
- Skilled in deploying ML/DL models at scale on public cloud and/or on-prem HPC clusters in production
- Demonstrated C/C++ programming proficiency with understanding of software design, algorithms, and performance optimizations
- Familiarity with NVIDIA GPU architectures
- GPU development experience using NVIDIA CUDA‑x libraries, cuBLAS, cuDNN
- Knowledge of MLOps technologies such as containers, data center deployments, and cluster management software
- Experience working with enterprise developers building HPC or data analytics applications
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
