Full-Time

Solutions Architect

Financial Services

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$148k - $287.5kAnnually

+ Equity

Senior

Remote in USA + 1 more

More locations: New York, NY, USA

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Python
Tensorflow
Pytorch
Apache Spark
Machine Learning
C/C++

You match the following NVIDIA's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • BS/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 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
Responsibilities
  • Perform proof-of-concepts working side by side with clients, engineers, and other architects on in-depth analysis and optimization of powerful AI models to ensure the best performance on current- and next-generation GPU architectures.
  • Work directly with client Data Scientists and developers on business-impacting workflows, projects, issues and success using NVIDIA technology.
  • Build collateral (notebook/ blog) applied to Finance industry use-cases such as Generative AI, recommender, GAN, GNN, monte-carlo, Quantitative Finance, etc. by working closely with customers.
  • Collaborate with key industry partners/customer developers to build GPU-accelerated solutions that are applied to their products and technologies.
  • Partner with NVIDIA Engineering, Product Engineering, 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.
Desired Qualifications
  • Skilled in deploying ML/DL models at scale on public cloud computing clusters in production
  • Development experience with NVIDIA software libraries and GPUs
  • Knowledge of MLOps technologies such as Docker/containers, Kubernetes, KubeFlow, data center deployments etc.
  • Experience working with enterprise developers building AI, HPC, or data analytics applications

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA stands out from competitors by offering a combination of hardware and software solutions, including cloud-based services like NVIDIA CloudXR and NGC, which enable scalable applications in AI and machine learning. The company's goal is to drive innovation in AI and computing technologies, ensuring they provide advanced solutions for a wide range of clients, from gamers to enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

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Benefits

Company Equity

401(k) Company Match