below marketmost similar roles pay hereabove market
This role pays more than
53%
of similar roles. Most pay
$162,000–$235,750
— the blue band above.
At the midpoint, this role pays about
$197k
versus about
$199k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
JOB TITLE: Solutions Architect, Financial Services Capital Markets
The Solutions Architect, Financial Services Capital Markets joins the Financial Services Solution Architect team to work alongside Quants and Data Scientists. This role involves partnering with engineering, product, and sales teams to secure design wins and enable product feature growth through customer feedback and proof-of-concept evaluations. You will perform in-depth analysis, profiling, and optimization of machine learning and deep learning models on current and next-generation GPU architectures. Key responsibilities include building collateral like notebooks and blogs for use cases such as Monte-Carlo simulations and quantitative finance. Required skills include Python, C++, PyTorch, Spark, Dask, Jax, and TensorFlow. You must be able to deploy models at scale on public cloud or on-prem HPC clusters, utilizing CUDA-x libraries, cuBLAS, cuDNN, and MLOps technologies.
What does a Solutions Architect earn in California?
Median $235750 from 57 postings across 11 companies.
Partner with internal engineering, product, and sales teams to secure design wins at customer sites.
Enable product feature growth by gathering customer feedback and conducting proof-of-concept evaluations.
Perform in-depth analysis, profiling, and optimization of ML/DL models for current and next-generation GPU architectures.
Work directly with client researchers and engineers to resolve business-impacting workflows and technical issues.
Facilitate rapid resolution of customer issues to ensure high levels of customer satisfaction.
Build technical collateral like notebooks and blogs for finance use-cases including GNNs and Monte-Carlo simulations.
Deploy ML/DL models at scale on public cloud computing and on-prem HPC clusters in production.
What we're looking for
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 and C++.
Experience with ML/DL algorithms using frameworks such as PyTorch, Spark, Dask, Jax, or TensorFlow.
Ability to communicate ideas and share code clearly through blog posts and GitHub.
Effective verbal/written communication and technical presentation skills.
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 (preferred).
Familiarity with NVIDIA GPU architectures and GPU Development experience through NVIDIA CUDA-x libraries, cuBLAS, and cuDNN (preferred).
AWS
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Cloud Computing
Microservices
SaaS
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Agile
Full-stack Development
System Design
Network Diagrams
Security Controls
Digital Transformation
Software Development