Solutions Architect, AI and ML at NVIDIA

Redmond, Washington, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial Intelligence, Cloud ComputingIndustries

Requirements

3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful
BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience
Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
Ability to use at least one scripting language (i.e., Python)
Good programming and debugging skills
Ability to communicate your ideas/code clearly through documents, presentations etc

Responsibilities

Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms
Build custom PoCs for solutions that address customer’s critical business needs applying NVIDIA hardware and software technology
Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions
Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc
Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies
Establish close technical ties to the customer to facilitate rapid resolution of customer issues

Skills

Key technologies and capabilities for this role

Machine LearningDeep LearningGPUCloud ComputingData AnalyticsAISolutions ArchitectureProof of ConceptNVIDIA SoftwareData Science

Questions & Answers

Common questions about this position

What experience is required for the Solutions Architect role?

Candidates need 3+ years of Solutions Engineering or similar Sales Engineering roles, plus 3+ years in Deep Learning and Machine Learning including frameworks like TensorFlow or PyTorch, with GPU and CUDA experience being extremely helpful. A BS/MS/PhD in fields like Electrical/Computer Engineering, Computer Science, Statistics, Physics, or equivalent experience is required.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What are some ways to stand out as a candidate?

Having an AWS, GCP, or Azure Professional Solution Architect Certification and hands-on experience with NVIDIA GPUs will help you stand out.

What does the Solutions Architecture team at NVIDIA do?

The team works with exciting computing hardware and software technologies including breakthroughs in machine learning and data science, serving as the first line of technical expertise between NVIDIA and customers, engaging with developers, researchers, data scientists, and business/engineering teams.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

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 products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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